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A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future

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Abstract

With the advent of Minimally Invasive Surgery (MIS), intra-operative imaging has become crucial for surgery and therapy guidance, allowing to partially compensate for the lack of information typical of MIS. This paper reviews the advancements in both classical (i.e. ultrasounds, X-ray, optical coherence tomography and magnetic resonance imaging) and more recent (i.e. multispectral, photoacoustic and Raman imaging) intra-operative imaging modalities. Each imaging modality was analyzed, focusing on benefits and disadvantages in terms of compatibility with the operating room, costs, acquisition time and image characteristics. Tables are included to summarize this information. New generation of hybrid surgical room and algorithms for real time/in room image processing were also investigated. Each imaging modality has its own (site- and procedure-specific) peculiarities in terms of spatial and temporal resolution, field of view and contrasted tissues. Besides the benefits that each technique offers for guidance, considerations about operators and patient risk, costs, and extra time required for surgical procedures have to be considered. The current trend is to equip surgical rooms with multimodal imaging systems, so as to integrate multiple information for real-time data extraction and computer-assisted processing. The future of surgery is to enhance surgeons eye to minimize intra- and after-surgery adverse events and provide surgeons with all possible support to objectify and optimize the care-delivery process.

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Notes

  1. https://www.healthcare.siemens.com/clinical-specialities/surgery/experience-hybrid-or/360-tour.

  2. https://www.imris.com.

References

  1. Abul-Kasim, K., M. Söderberg, E. Selariu, M. Gunnarsson, M. Kherad, and A. Ohlin. Optimization of radiation exposure and image quality of the cone-beam o-arm intraoperative imaging system in spinal surgery. Clin. Spine Surg. 25(1):52–58, 2012.

    Google Scholar 

  2. Abu-Zidan, F. M., A. F. Hefny, and P. Corr. Clinical ultrasound physics. J. Emerg. Trauma Shock 4(4):501, 2011.

    PubMed  PubMed Central  Google Scholar 

  3. Ahmadi, S.-A., F. Milletari, N. Navab, M. Schuberth, A. Plate, and K. Bötzel. 3D transcranial ultrasound as a novel intra-operative imaging technique for DBS surgery: a feasibility study. Int. J. Comput. Assist. Radiol. Surg. 10:891–900, 2015.

    PubMed  Google Scholar 

  4. Ahrar, K., S. H. Sabir, S. M. Yevich, R. A. Sheth, J. U. Ahrar, A. L. Tam, and J. R. Stafford. MRI-guided interventions in musculoskeletal system. Top. Magn. Reson. Imaging 27(3):129–139, 2018.

    PubMed  Google Scholar 

  5. Alam, I. S., I. Steinberg, O. Vermesh, N. S. van den Berg, E. L. Rosenthal, G. M. van Dam, V. Ntziachristos, S. S. Gambhir, S. Hernot, and S. Rogalla. Emerging intraoperative imaging modalities to improve surgical precision. Mol. Imaging Biol. 20:705–715, 2018.

    PubMed  Google Scholar 

  6. Alenezi, A. N. and O. Karim. Role of intra-operative contrast-enhanced ultrasound (CEUS) in robotic-assisted nephron-sparing surgery. J. Robot. Surg. 9(1):1–10, 2015.

    PubMed  PubMed Central  Google Scholar 

  7. Alfonso-Garcia, A., J. Bec, S. Sridharan Weaver, B. Hartl, J. Unger, M. Bobinski, M. Lechpammer, F. Girgis, J. Boggan, and L. Marcu. Real-time augmented reality for delineation of surgical margins during neurosurgery using autofluorescence lifetime contrast. J. Biophotonics 13(1):e201900108, 2020.

    CAS  PubMed  Google Scholar 

  8. Alfonso, F., M. Paulo, N. Gonzalo, J. Dutary, P. Jimenez-Quevedo, V. Lennie, J. Escaned, C. Bañuelos, R. Hernandez, and C. Macaya. Diagnosis of spontaneous coronary artery dissection by optical coherence tomography. J. Am. Coll. Cardiol. 59(12):1073–1079, 2012.

    PubMed  Google Scholar 

  9. Allard, M., J. Shubert, and M. A. L. Bell. Feasibility of photoacoustic-guided teleoperated hysterectomies. J. Med. Imaging 5(2):021213, 2018.

    Google Scholar 

  10. Andreozzi, J. M., R. Zhang, D. J. Gladstone, B. B. Williams, A. K. Glaser, B. W. Pogue, and L. A. Jarvis. Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy. Med. Phys. 43(2):993–1002, 2016.

    PubMed  PubMed Central  Google Scholar 

  11. Antico, M., F. Sasazawa, L. Wu, A. Jaiprakash, J. Roberts, R. Crawford, A. K. Pandey, and D. Fontanarosa. Ultrasound guidance in minimally invasive robotic procedures. Med. Image Anal. 54:149, 2019.

    PubMed  Google Scholar 

  12. Ashour, R., S. Reintjes, M. S. Park, S. Sivakanthan, H. van Loveren, and S. Agazzi. Intraoperative magnetic resonance imaging in skull base surgery: a review of 71 consecutive cases. World Neurosurg. 93:183–190, 2016.

    PubMed  Google Scholar 

  13. Ayala, L., S. Wirkert, M. Herrera, A. Hernández-Aguilera, A. Vermuri, E. Santos, and L. Maier-Hein. Multispectral imaging enables visualization of spreading depolarizations in gyrencephalic brain. In: Bildverarbeitung für die Medizin 2019 edited by H. Handels, T. M. Deserno, A. Maier, K. H. Maier-Hein, C. Palm. Cham: Springer, 2019, pp. 244–244.

    Google Scholar 

  14. Barkhausen, J., T. Kahn, G. A. Krombach, C. K. Kuhl, J. Lotz, D. Maintz, J. Ricke, S. O. Schoenberg, T. J. Vogl, and F. K. Wacker. White paper: Interventional MRI: Current status and potential for development considering economic perspectives, part 1: General application. Natl. Libraray Med. 189:611–623, 2017

    Google Scholar 

  15. Barsa, P., R. Frőhlich, V. Beneš, and P. Suchomel. Intraoperative portable CT-scanner based spinal navigation-a feasibility and safety study. Acta Neurochir. 156(9):1807–1812, 2014.

    PubMed  Google Scholar 

  16. Barsa, P., R. Frőhlich, M. Šercl, P. Buchvald, and P. Suchomel. The intraoperative portable ct scanner-based spinal navigation: a viable option for instrumentation in the region of cervico-thoracic junction. Eur. Spine J. 25(6):1643–1650, 2016.

    PubMed  Google Scholar 

  17. Becker, D., T. Wray, and J. Hart. Ultrasonic intracavity probe for 3D imaging. US Patent 9,808,221, 2017.

  18. Bell, R. B. Computer planning and intraoperative navigation in orthognathic surgery. J. Oral Maxillofac. Surg. 69(3):592–605, 2011.

    PubMed  Google Scholar 

  19. Bell, M. A. L., X. Guo, D. Y. Song, and E. M. Boctor. Transurethral light delivery for prostate photoacoustic imaging. J. Biomed. Opt. 20(3):036002, 2015.

    Google Scholar 

  20. Bell, M. A. L., A. K. Ostrowski, K. Li, P. Kazanzides, and E. M. Boctor. Localization of transcranial targets for photoacoustic-guided endonasal surgeries. Photoacoustics 3(2):78–87, 2015.

    Google Scholar 

  21. Bernhardt, S., S. A. Nicolau, L. Soler, and C. Doignon. The status of augmented reality in laparoscopic surgery as of 2016. Med. Image Anal. 37:66–90, 2017.

    PubMed  Google Scholar 

  22. Bluemel, C., K. Herrmann, A. Kübler, A. K. Buck, E. Geissinger, V. Wild, S. Hartmann, C. Lapa, C. Linz, and U. Müller-Richter. Intraoperative 3-d imaging improves sentinel lymph node biopsy in oral cancer. Eur. J. Nucl. Med. Mol. Imaging 41(12):2257–2264, 2014.

    CAS  PubMed  Google Scholar 

  23. Boda-Heggemann, J., J. Fleckenstein, F. Lohr, H. Wertz, M. Nachit, M. Blessing, D. Stsepankou, I. Lob, B. Kupper, A. Kavanagh, V. N. Hansen, M. Brada, F. Wenz, and H. McNair. Multiple breath-hold CBCT for online image guided radiotherapy of lung tumors: simulation with a dynamic phantom and first patient data. Radiother. Oncol. 98(3):309–316, 2011.

    PubMed  Google Scholar 

  24. Bozzao, A., A. Romano, A. Angelini, G. D’Andrea, L. F. Calabria, V. Coppola, L. Mastronardi, L. M. Fantozzi, and L. Ferrante. Identification of the pyramidal tract by neuronavigation based on intraoperative magnetic resonance tractography: correlation with subcortical stimulation. Eur. Radiol. 20(10):2475–2481, 2010.

    PubMed  Google Scholar 

  25. Brattain, L. J., P. M. Loschak, C. M. Tschabrunn, E. Anter, and R. D. Howe. Instrument tracking and visualization for ultrasound catheter guided procedures,” in: Workshop on Augmented Environments for Computer-Assisted Interventions:41–50, Springer, Cham (2014)

  26. Buchfelder, M. and S.-M. Schlaffer. Intraoperative magnetic resonance imaging for pituitary adenomas,” in Buchfelder, M., Guaraldi, F. (eds) Imaging in Endocrine Disorders 45:121–132, Karger Publishers, Basel (2016).

    Google Scholar 

  27. Burchiel, K. J., S. McCartney, A. Lee, and A. M. Raslan. Accuracy of deep brain stimulation electrode placement using intraoperative computed tomography without microelectrode recording. J. Neurosurg. 119(2):301–306, 2013.

    PubMed  Google Scholar 

  28. Bus, M. T., B. G. Muller, D. M. de Bruin, D. J. Faber, G. M. Kamphuis, T. G. van Leeuwen, T. M. de Reijke, and J. J. de la Rosette. Volumetric in vivo visualization of upper urinary tract tumors using optical coherence tomography: a pilot study. J. Urol. 190(6):2236–2242, 2013.

    PubMed  Google Scholar 

  29. Cardenas, C. E., J. Yang, B. M. Anderson, L. E. Court, and K. B. Brock. Advances in auto-segmentation,” in Semin. Radiat. Oncol., 29, 185–197, 2019.

    PubMed  Google Scholar 

  30. Carrasco-Zevallos, O., B. Keller, C. Viehland, L. Shen, G. Waterman, B. Todorich, C. Shieh, P. Hahn, S. Farsiu, A. Kuo, C. A. Toth, and J. A. Izatt. Live volumetric (4D) visualization and guidance of in vivo human ophthalmic surgery with intraoperative optical coherence tomography. Sci. Rep. 6:31689, 2016.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Carrasco-Zevallos, O. M., C. Viehland, B. Keller, M. Draelos, A. N. Kuo, C. A. Toth, and J. A. Izatt. Review of intraoperative optical coherence tomography: technology and applications. Biomed. Opt. Express 8(3):1607–1637, 2017.

    PubMed  PubMed Central  Google Scholar 

  32. Chakraborty, S., S. Zavarella, S. Salas, and M. Schulder. Intraoperative mri for resection of intracranial meningiomas.” J. Exp. Therap. Oncol., 12(2):157162, 2017.

    Google Scholar 

  33. Chen, Z. and Q. Huang. Real-time freehand 3d ultrasound imaging. Comput. Methods Biomech. Biomed. Eng. 6(1):74–83, 2018.

    Google Scholar 

  34. Chevrier, M.-C., J. David, M. El Khoury, L. Lalonde, M. Labelle, and I. Trop. Breast biopsies under magnetic resonance imaging guidance: challenges of an essential but imperfect technique. Curr. Probl. Diagn. Radiol. 45(3):193–204, 2016.

    PubMed  Google Scholar 

  35. Chopra, S., A. M. Bove, and I. S. Gill. Robotic partial nephrectomy: Advanced techniques and use of intraoperative imaging,” in Su LM (ed) Atlas of Robotic Urologic Surgery:93–101, Springer, Cham (2017)

    Google Scholar 

  36. Chopra, S., J. Rump, S. Schmidt, F. Streitparth, C. Seebauer, G. Schumacher, I. Van der Voort, and U. Teichgräber. Imaging sequences for intraoperative MR-guided laparoscopic liver resection in 1.0-T high field open MRI. Eur. Radiol. 19(9):2191–2196, 2009.

    CAS  PubMed  Google Scholar 

  37. Choudhri, A. F., A. Siddiqui, P. Klimo, and F. A. Boop. Intraoperative mri in pediatric brain tumors. Pediatr. Radiol. 45:397–405, 2015.

    Google Scholar 

  38. Chu, C. R., A. Williams, D. Tolliver, C. K. Kwoh, S. Bruno III, and J. J. Irrgang. Clinical optical coherence tomography of early articular cartilage degeneration in patients with degenerative meniscal tears. Arthritis Rheumatism 62(5):1412–1420, 2010.

    PubMed  Google Scholar 

  39. Cialla-May, D., X.-S. Zheng, K. Weber, and J. Popp. Recent progress in surface-enhanced Raman spectroscopy for biological and biomedical applications: from cells to clinics. Chem. Soc. Rev. 46(13):3945–3961, 2017.

    CAS  PubMed  Google Scholar 

  40. Clancy, N. T., S. Arya, D. Stoyanov, M. Singh, G. B. Hanna, and D. S. Elson. Intraoperative measurement of bowel oxygen saturation using a multispectral imaging laparoscope. Biomed. Opt. Express 6(10):4179–4190, 2015.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Clancy, N. T., G. Jones, L. Maier-Hein, D. S. Elson, and D. Stoyanov. Surgical spectral imaging. Med. Image Anal. 63:101699, 2020.

    PubMed  Google Scholar 

  42. Clancy, N. T., S. Saso, D. Stoyanov, V. Sauvage, D. J. Corless, M. Boyd, D. E. Noakes, M.-Y. Thum, S. Ghaem-Maghami, J. R. Smith, and D. S. Elson. Multispectral imaging of organ viability during uterine transplantation surgery in rabbits and sheep. J. Biomed. Opt. 21(10):106006, 2016.

    PubMed  Google Scholar 

  43. Coburger, J., A. Merkel, M. Scherer, F. Schwartz, F. Gessler, C. Roder, A. Pala, R. König, L. Bullinger, G. Nagel, C. Jungk, S. Bisdas, A. Nabavi, O. Ganslandt, V. Seifert, M. Tatagiba, C. Senft, M. Mehdorn, A. W. Unterberg, K. Rossler, and C. Rainer Wirtz. Low-grade glioma surgery in intraoperative magnetic resonance imaging: results of a multicenter retrospective assessment of the german study group for intraoperative magnetic resonance imaging. Neurosurgery 78(6):775–786, 2015.

    Google Scholar 

  44. Coburger, J. and C. R. Wirtz. Fluorescence guided surgery by 5-ala and intraoperative mri in high grade glioma: a systematic review. J. Neurooncol. 141(3):533–546, 2019.

    CAS  PubMed  Google Scholar 

  45. Colleoni, E., S. Moccia, X. Du, E. De Momi, and D. Stoyanov. Deep learning based robotic tool detection and articulation estimation with spatio-temporal layers. IEEE Robot. Autom. Lett. 4(3):2714–2721, 2019.

    Google Scholar 

  46. Cooke, D. L., M. Levitt, L. Kim, D. Hallam, and B. Ghodke. Transcranial access using fluoroscopic flat panel detector ct navigation. Am. J. Neuroradiol. 32(4):E69–E70, 2011.

    CAS  PubMed  Google Scholar 

  47. Coste, C., Y. Asloum, P. Marcheix, P. Dijoux, J. Charissoux, and C. Mabit. Percutaneous iliosacral screw fixation in unstable pelvic ring lesions: the interest of O-ARM CT-guided navigation. Orthopaed. Traumatol. 99(4):S273–S278, 2013.

    CAS  Google Scholar 

  48. Crane, L. M., G. Themelis, R. G. Pleijhuis, N. J. Harlaar, A. Sarantopoulos, H. J. Arts, A. G. van der Zee, N. Vasilis, and G. M. van Dam. Intraoperative multispectral fluorescence imaging for the detection of the sentinel lymph node in cervical cancer: a novel concept. Mol. Imaging Biol. 13(5):1043–1049, 2011.

    PubMed  Google Scholar 

  49. Cui, Z., L. Pan, H. Song, X. Xu, B. Xu, X. Yu, and Z. Ling. Intraoperative mri for optimizing electrode placement for deep brain stimulation of the subthalamic nucleus in parkinson disease. J. Neurosurg. 124(1):62–69, 2016.

    PubMed  Google Scholar 

  50. Cunningham, B., K. Jackson, and G. Ortega. Intraoperative CT in the assessment of posterior wall acetabular fracture stability. Orthopedics 37(4):e328–e331, 2014.

    PubMed  Google Scholar 

  51. Das, S., M. K. Kummelil, V. Kharbanda, V. Arora, S. Nagappa, R. Shetty, and B. K. Shetty. Microscope integrated intraoperative spectral domain optical coherence tomography for cataract surgery: uses and applications. Curr. Eye Res. 41(5):643–652, 2016.

    PubMed  Google Scholar 

  52. De Lorenzo, D., A. Vaccarella, G. Khreis, H. Moennich, G. Ferrigno, and E. De Momi. Accurate calibration method for 3D freehand ultrasound probe using virtual plane. Med. Phys. 38(12):6710–6720, 2011.

    PubMed  Google Scholar 

  53. Dima, A., J. Gateau, J. Claussen, D. Wilhelm, and V. Ntziachristos. Optoacoustic imaging of blood perfusion: techniques for intraoperative tissue viability assessment. J. Biophotonics 6(6-7):485–492, 2013.

    CAS  PubMed  Google Scholar 

  54. Dinesh, S. K., R. Tiruchelvarayan, and I. Ng. A prospective study on the use of intraoperative computed tomography (iCT) for image-guided placement of thoracic pedicle screws. Br. J. Neurosurg. 26(6):838–844, 2012.

    PubMed  Google Scholar 

  55. Diodato, A., A. Cafarelli, A. Schiappacasse, S. Tognarelli, G. Ciuti, and A. Menciassi. Motion compensation with skin contact control for high intensity focused ultrasound surgery in moving organs. Phys. Med. Biol. 63(3):035017, 2018.

    CAS  PubMed  Google Scholar 

  56. Diot, G., S. Metz, A. Noske, E. Liapis, B. Schroeder, S. V. Ovsepian, R. Meier, E. J. Rummeny, and V. Ntziachristos. Multi-spectral optoacoustic tomography (msot) of human breast cancer. Clin. Cancer Res., 23, 6912-6922, 2017.

    CAS  PubMed  Google Scholar 

  57. Ehlers, J. P., A. Uchida, and S. K. Srivastava. Intraoperative optical coherence tomography-compatible surgical instruments for real-time image-guided ophthalmic surgery. Br. J. Ophthalmol., 101): 1306-1308, 2017.

    PubMed  PubMed Central  Google Scholar 

  58. Eitel, C., G. Hindricks, M. Grothoff, M. Gutberlet, and P. Sommer. Catheter ablation guided by real-time MRI. Curr. Cardiol. Rep. 16(8):511, 2014.

    PubMed  Google Scholar 

  59. Ermolayev, V., X. L. Dean-Ben, S. Mandal, V. Ntziachristos, and D. Razansky. Simultaneous visualization of tumour oxygenation, neovascularization and contrast agent perfusion by real-time three-dimensional optoacoustic tomography. Eur. Radiol. 26(6):1843–1851, 2016.

    PubMed  Google Scholar 

  60. Fabelo, H., S. Ortega, R. Lazcano, D. Madroñal, G. M Callicó, E. Juárez, R. Salvador, D. Bulters, H. Bulstrode, A. Szolna, J. F. Pineiro, C. Sosa, A. J. O’Shanahan, S. Bisshopp, M. Hernandez, J. Morera, D. Ravi, R. Kiran, A. Vega, A. Baez-Quevedo, G.-Z. Yang, B. Stanciulescu, and R. Sarmiento. An intraoperative visualization system using hyperspectral imaging to aid in brain tumor delineation. Sensors 18(2):430, 2018.

    Google Scholar 

  61. Falkner-Radler, C. I., C. Glittenberg, S. Hagen, T. Benesch, and S. Binder. Spectral-domain optical coherence tomography for monitoring epiretinal membrane surgery. Ophthalmology 117(4):798–805, 2010.

    PubMed  Google Scholar 

  62. Farnia, P., A. Ahmadian, T. Shabanian, N. D. Serej, and J. Alirezaie. Brain-shift compensation by non-rigid registration of intra-operative ultrasound images with preoperative MR images based on residual complexity. Int. J. Comput. Assist. Radiol. Surg. 10:555–562, 2015.

    CAS  PubMed  Google Scholar 

  63. Ferrante, G., P. Presbitero, R. Whitbourn, and P. Barlis. Current applications of optical coherence tomography for coronary intervention. Int. J. Cardiol. 165(1):7–16, 2013.

    PubMed  Google Scholar 

  64. Fetterly, K. A., V. Mathew, R. Lennon, M. R. Bell, D. R. Holmes Jr, and C. S. Rihal. Radiation dose reduction in the invasive cardiovascular laboratory: implementing a culture and philosophy of radiation safety. JACC 5(8):866–873, 2012.

    PubMed  Google Scholar 

  65. Fitts, J., P. Lee, P. Hofmaster, D. Malenka, et al. Fluoroscopy-guided femoral artery puncture reduces the risk of pci-related vascular complications. J. Interv. Cardiol. 21(3):273–278, 2008

    PubMed  Google Scholar 

  66. Garai, E., S. Sensarn, C. L. Zavaleta, N. O. Loewke, S. Rogalla, M. J. Mandella, S. A. Felt, S. Friedland, J. T. Liu, S. S. Gambhir, and C. H. Contag. A real-time clinical endoscopic system for intraluminal, multiplexed imaging of surface-enhanced Raman scattering nanoparticles. PLoS ONE 10(4):e0123185, 2015.

    PubMed  PubMed Central  Google Scholar 

  67. Ghosh, D., N. V. Michalopoulos, T. Davidson, F. Wickham, N. R. Williams, and M. R. Keshtgar. Sentinel node detection in early breast cancer with intraoperative portable gamma camera: UK experience. Breast 32:53–59, 2017.

    PubMed  Google Scholar 

  68. Gieroba, T. J., G. I. Bain, and P. J. Cundy. Review of the clinical use of fluoroscopy in hand surgery. Hand Surg. 20(02):228–236, 2015.

    PubMed  Google Scholar 

  69. Ginat, D. T., B. Swearingen, W. Curry, D. Cahill, J. Madsen, and P. W. Schaefer. 3 tesla intraoperative mri for brain tumor surgery. J. Magn. Reson. Imaging 39(6):1357–1365, 2014.

    PubMed  Google Scholar 

  70. Golub, D., J. Hyde, S. Dogra, J. Nicholson, K. A. Kirkwood, P. Gohel, S. Loftus, and T. H. Schwartz. Intraoperative mri versus 5-ala in high-grade glioma resection: a network meta-analysis. J. Neurosurg., 1, 1–15, 2020.

    Google Scholar 

  71. Gonzalo, N., J. Escaned, F. Alfonso, C. Nolte, V. Rodriguez, P. Jimenez-Quevedo, C. Bañuelos, A. Fernández-Ortiz, E. Garcia, R. Hernandez-Antolin, and C. Macaya. Morphometric assessment of coronary stenosis relevance with optical coherence tomography: a comparison with fractional flow reserve and intravascular ultrasound. J. Am. Coll. Cardiol. 59(12):1080–1089, 2012.

    PubMed  Google Scholar 

  72. Gorpas, D., J. Phipps, J. Bec, D. Ma, S. Dochow, D. Yankelevich, J. Sorger, J. Popp, A. Bewley, R. Gandour-Edwards, et al.. Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients. Sci. Rep. 9(1):1–9, 2019.

    CAS  Google Scholar 

  73. Guo, Z., M. C.-W. Leong, H. Su, K.-W. Kwok, D. T.-M. Chan, and W.-S. Poon. Techniques for stereotactic neurosurgery: Beyond the frame, toward the intraoperative magnetic resonance imaging–guided and robot-assisted approaches. World Neurosurg. 116:77–87, 2018.

    PubMed  Google Scholar 

  74. Hahn, P., J. Migacz, R. O’Connell, R. S. Maldonado, J. A. Izatt, and C. A. Toth. The use of optical coherence tomography in intraoperative ophthalmic imaging. Ophthal. Surg. Lasers Imaging Retina 42(4):S85–S94, 2011.

    Google Scholar 

  75. Hall, N. C., S. P. Povoski, J. Zhang, M. V. Knopp, and E. W. Martin Jr. Use of intraoperative nuclear medicine imaging technology: strategy for improved patient management. Expert Rev. Med. Devices 10(2):149–152, 2013.

    CAS  PubMed  Google Scholar 

  76. Han, Y., G. Y. Hou, S. Wang, and E. Konofagou. High intensity focused ultrasound (HIFU) focal spot localization using harmonic motion imaging (HMI). Phys. Med. Biol. 60(15):5911, 2015.

    PubMed  PubMed Central  Google Scholar 

  77. Hanlon, E., R. Manoharan, T. Koo, K. Shafer, J. Motz, M. Fitzmaurice, J. Kramer, I. Itzkan, R. Dasari, and M. Feld. Prospects for in vivo raman spectroscopy. Phys. Med. Biol. 45(2):R1, 2000.

    CAS  PubMed  Google Scholar 

  78. Hansen, K. L., M. M. Pedersen, H. Møller-Sørensen, J. Kjaergaard, J. C. Nilsson, J. T. Lund, J. A. Jensen, and M. B. Nielsen. Intraoperative cardiac ultrasound examination using vector flow imaging. Ultrason. Imaging 35(4):318–332, 2013.

    PubMed  Google Scholar 

  79. Harmsen, S., R. Huang, M. A. Wall, H. Karabeber, J. M. Samii, M. Spaliviero, J. R. White, S. Monette, R. O’Connor, K. L. Pitter, S. W. Lowe, R. G. Blasberg, and M. F. Kircher. Surface-enhanced resonance Raman scattering nanostars for high-precision cancer imaging. Sci. Transl. Med. 7(271):271ra7–271ra7, 2015.

    PubMed  PubMed Central  Google Scholar 

  80. Hashemi, R. H., W. G. Bradley, and C. J. Lisanti, MRI: The Basics. Lippincott Williams & Wilkins, 2012.

    Google Scholar 

  81. Hekman, M. C., M. Rijpkema, J. F. Langenhuijsen, O. C. Boerman, E. Oosterwijk, and P. F. Mulders. Intraoperative imaging techniques to support complete tumor resection in partial nephrectomy. Eur. Urol. Focus, 2017; 4, 960–968.

    PubMed  Google Scholar 

  82. Heller, S. and P. Zanzonico. Nuclear probes and intraoperative gamma cameras,” in Semin. Nucl. Med., 41, 166–181, 2011.

    PubMed  Google Scholar 

  83. Hlavac, M., C. R. Wirtz, and M.-E. Halatsch. Intraoperative magnetic resonance imaging. HNO 65:25–29, 2017.

    CAS  PubMed  Google Scholar 

  84. Holzer, M. S., S. L. Best, N. Jackson, A. Thapa, G. V. Raj, J. A. Cadeddu, and K. J. Zuzak. Assessment of renal oxygenation during partial nephrectomy using hyperspectral imaging. J. Urol. 186(2):400–404, 2011.

    PubMed  Google Scholar 

  85. Huang, D., E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, and C. A. Puliafito. Optical coherence tomography. Science 254(5035):1178–1181, 1991.

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Huang, Q. and Z. Zeng. A review on real-time 3D ultrasound imaging technology. BioMed Res. Int. 17:6027029, 2017.

    PubMed  PubMed Central  Google Scholar 

  87. Imbault, M., D. Chauvet, J.-L. Gennisson, L. Capelle, and M. Tanter. Intraoperative functional ultrasound imaging of human brain activity. Sci. Rep. 7(1):7304, 2017.

    PubMed  PubMed Central  Google Scholar 

  88. Imola, F., M. T. Mallus, V. Ramazzotti, A. Manzoli, A. Pappalardo, A. Di Giorgio, M. Albertucci, and F. Prati. Safety and feasibility of frequency domain optical coherence tomography to guide decision making in percutaneous coronary intervention. EuroIntervention 6(5):575–581, 2010.

    PubMed  Google Scholar 

  89. Ing, F. “Delivery of stents to target lesions: Techniques of intraoperative stent implantation and intraoperative angiograms. Pediatr. Cardiol. 26:260–266, 2005.

    CAS  PubMed  Google Scholar 

  90. Iturri-Clavero, F., L. Galbarriatu-Gutierrez, A. Gonzalez-Uriarte, G. Tamayo-Medel, K. de Orte, A. Martinez-Ruiz, K. Castellon-Larios, and S. Bergese. “low-field” intraoperative MRI: a new scenario, a new adaptation. Clin. Radiol. 71(11):1193–1198, 2016.

    CAS  PubMed  Google Scholar 

  91. Jaffray, D. A. “Image-guided radiotherapy: from current concept to future perspectives. Nat. Rev. Clin. Oncol. 9(12):688, 2012.

    CAS  PubMed  Google Scholar 

  92. Jakobs, M., E. Krasniqi, M. Kloß, J.-O. Neumann, B. Campos, A. W. Unterberg, and K. L. Kiening. Intraoperative stereotactic magnetic resonance imaging for deep brain stimulation electrode planning in patients with movement disorders. World Neurosurg. 119:e801–e808, 2018.

    PubMed  Google Scholar 

  93. Jarvis, L. A., R. Zhang, D. J. Gladstone, S. Jiang, W. Hitchcock, O. D. Friedman, A. K. Glaser, M. Jermyn, and B. W. Pogue. Cherenkov video imaging allows for the first visualization of radiation therapy in real time. Int. J. Radiat. Oncol. Biol. Phys. 89(3):615–622, 2014.

    PubMed  Google Scholar 

  94. Jolesz, F. A. Intraoperative imaging in neurosurgery: where will the future take us? Intraoper. Imaging 109:21–25, 2011.

    Google Scholar 

  95. Kapur, T., J. Egger, A. Damato, E. J. Schmidt, and A. N. Viswanathan. 3-T MR-guided brachytherapy for gynecologic malignancies. Magn. Reson. Imaging 30(9):1279–1290, 2012.

    PubMed  PubMed Central  Google Scholar 

  96. Kenngott, H. G., M. Wagner, M. Gondan, F. Nickel, M. Nolden, A. Fetzer, J. Weitz, L. Fischer, S. Speidel, H.-P. Meinzer, D. Bockler, M. W. Buchler, and B. P. Muller-Stich. Real-time image guidance in laparoscopic liver surgery: first clinical experience with a guidance system based on intraoperative ct imaging. Surg. Endosc. 28(3):933–940, 2014.

    PubMed  Google Scholar 

  97. King, D. R.,W. Li, J. J. Squiers, R. Mohan, E. Sellke, W. Mo, X. Zhang, W. Fan, J. M. DiMaio, and J. E. Thatcher. Surgical wound debridement sequentially characterized in a porcine burn model with multispectral imaging. Burns 41(7):1478–1487, 2015.

    PubMed  Google Scholar 

  98. Kircher, M. F., A. De La Zerda, J. V. Jokerst, C. L. Zavaleta, P. J. Kempen, E. Mittra, K. Pitter, R. Huang, C. Campos, F. Habte, R. Sinclair, M. I. K. Brennan, Cameron W and, E. C. Holland, and S. S Gambhir. A brain tumor molecular imaging strategy using a new triple-modality MRI-photoacoustic-Raman nanoparticle. Nat. Med. 18(5):829, 2012.

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Kirchner, T., F. Sattler, J. Gröhl, and L. Maier-Hein. Signed real-time delay multiply and sum beamforming for multispectral photoacoustic imaging. J. Imaging 4(10):121, 2018.

    Google Scholar 

  100. Koch, M. and V. Ntziachristos. Advancing surgical vision with fluorescence imaging. Annu. Rev. Med. 67:153–164, 2016.

    CAS  PubMed  Google Scholar 

  101. Kubo, T., Y. Ino, T. Tanimoto, H. Kitabata, A. Tanaka, and T. Akasaka. Optical coherence tomography imaging in acute coronary syndromes. Cardiol. Res. Pract. 2011:312978, 2011

    PubMed  PubMed Central  Google Scholar 

  102. Kumashiro, R., K. Konishi, T. Chiba, T. Akahoshi, S. Nakamura, M. Murata, M. Tomikawa, T. Matsumoto, Y. Maehara, and M. Hashizume. Integrated endoscopic system based on optical imaging and hyperspectral data analysis for colorectal cancer detection. Anticancer Res. 36(8):3925–3932, 2016.

    CAS  PubMed  Google Scholar 

  103. Labadie, R. F., R. Balachandran, J. H. Noble, G. S. Blachon, J. E. Mitchell, F. A. Reda, B. M. Dawant, and J. M. Fitzpatrick. Minimally invasive image-guided cochlear implantation surgery: First report of clinical implementation. The Laryngoscope 124(8):1915–1922, 2014.

    PubMed  PubMed Central  Google Scholar 

  104. Leclerc, P., C. Ray, L. Mahieu-Williame, L. Alston, C. Frindel, P.-F. Brevet, D. Meyronet, J. Guyotat, B. Montcel, and D. Rousseau. Machine learning-based prediction of glioma margin from 5-ala induced ppix fluorescence spectroscopy. Sci. Rep. 10(1):1–9, 2020.

    Google Scholar 

  105. Lee, L. J., A. L. Damato, and A. N. Viswanathan. Clinical outcomes of high-dose-rate interstitial gynecologic brachytherapy using real-time CT guidance. Brachytherapy 12(4):303–310, 2013.

    PubMed  Google Scholar 

  106. Lee, L. B. and S. K. Srivastava. Intraoperative spectral-domain optical coherence tomography during complex retinal detachment repair. Ophthal. Surg. Lasers Imaging Retina 42:71, 2011.

    Google Scholar 

  107. Li, Q., X. He, Y. Wang, H. Liu, D. Xu, and F. Guo. Review of spectral imaging technology in biomedical engineering: achievements and challenges. J. Biomed. Opt. 18(10):100901, 2013.

    PubMed  Google Scholar 

  108. Lin, J., N. T. Clancy, Y. Hu, J. Qi, T. Tatla, D. Stoyanov, L. Maier-Hein, and D. S. Elson. Endoscopic depth measurement and super-spectral-resolution imaging,” in International Conference on Medical Image Computing and Computer-Assisted Intervention:39–47, Springer, Cham (2017)

  109. Liney, G. P., B. Whelan, B. Oborn, M. Barton, and P. Keall. MRI-linear accelerator radiotherapy systems. Clin. Oncol. 30(11):686–691, 2018.

    CAS  Google Scholar 

  110. Li, P., R. Qian, C. Niu, and X. Fu. Impact of intraoperative mri-guided resection on resection and survival in patient with gliomas: a meta-analysis. Curr. Med. Res. Opin. 33(4):621–630, 2017.

    PubMed  Google Scholar 

  111. Litjens, G., T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. Van Der Laak, B. Van Ginneken, and C. I. Sánchez. A survey on deep learning in medical image analysis. Med. Image Anal. 42:60–88, 2017.

    PubMed  Google Scholar 

  112. Li, R., P. Wang, L. Lan, F. P. Lloyd, C. J. Goergen, S. Chen, and J.-X. Cheng. Assessing breast tumor margin by multispectral photoacoustic tomography. Biomed. Opt. Express 6(4):1273–1281, 2015.

    PubMed  PubMed Central  Google Scholar 

  113. Lu, G. and B. Fei. Medical hyperspectral imaging: a review. J. Biomed. Opt. 19(1):010901, 2014.

    PubMed Central  Google Scholar 

  114. Lu, G., L. Halig, D. Wang, Z. G. Chen, and B. Fei. Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images. Int. Soc. Opt. Photon. 9036:90360S, 2014.

    Google Scholar 

  115. Lu, G., D. Wang, X. Qin, L. Halig, S. Muller, H. Zhang, A. Chen, B. W. Pogue, Z. G. Chen, and B. Fei. Framework for hyperspectral image processing and quantification for cancer detection during animal tumor surgery. J. Biomed. Opt. 20(12):126012, 2015.

    PubMed  PubMed Central  Google Scholar 

  116. Maier-Hein, L., S. S. Vedula, S. Speidel, N. Navab, R. Kikinis, A. Park, M. Eisenmann, H. Feussner, G. Forestier, S. Giannarou, M. Hashizume, D. Katic, H. Kenngott, M. Kranzfelder, A. Malpani, K. Marz, T. Neumuth, N. Padoy, C. Pugh, N. Schoch, S. Danail, R. Taylor, M. Wagner, G. D. Hager, and P. Jannin. Surgical data science for next-generation interventions. Nat. Biomed. Eng. 1(9):691, 2017.

    PubMed  Google Scholar 

  117. Majlesara, A., M. Golriz, M. Hafezi, A. Saffari, E. Stenau, L. Maier-Hein, B. P. Müller-Stich, and A. Mehrabi. Indocyanine green fluorescence imaging in hepatobiliary surgery. Photodiagn. Photodyn. Ther. 17:208–215, 2017.

    CAS  Google Scholar 

  118. Mascharak, S., B. J. Baird, and F. C. Holsinger. Detecting oropharyngeal carcinoma using multispectral, narrow-band imaging and machine learning. Laryngoscope 128:2514, 2018.

    PubMed  Google Scholar 

  119. Mathiassen, K., J. E. Fjellin, K. Glette, P. K. Hol, and O. J. Elle. An ultrasound robotic system using the commercial robot ur5. Front. Robot. AI 3:1, 2016.

    Google Scholar 

  120. Mehrtash, A., M. Ghafoorian, G. Pernelle, A. Ziaei, F. G. Heslinga, K. Tuncali, A. Fedorov, R. Kikinis, C. M. Tempany, W. M. Wells, P. Abolmaesumi, and T. Kapur. Automatic needle segmentation and localization in MRI with 3D convolutional neural networks: Application to MRI-targeted prostate biopsy. IEEE Trans. Med. Imaging 38:1026–1036, 2018.

    PubMed  PubMed Central  Google Scholar 

  121. Meola, A., F. Cutolo, M. Carbone, F. Cagnazzo, M. Ferrari, and V. Ferrari. Augmented reality in neurosurgery: a systematic review. Neurosurg. Rev. 40(4):537–548, 2017.

    PubMed  Google Scholar 

  122. Miller, S. E., W. S. Tummers, N. Teraphongphom, N. S. van den Berg, A. Hasan, R. D. Ertsey, S. Nagpal, L. D. Recht, E. D. Plowey, H. Vogel, et al.. First-in-human intraoperative near-infrared fluorescence imaging of glioblastoma using cetuximab-IRDye800. J. Neurooncol. 139(1):135–143, 2018.

    CAS  PubMed  PubMed Central  Google Scholar 

  123. Moccia, S., S. Foti, A. Routray, F. Prudente, A. Perin, R. F. Sekula, L. S. Mattos, J. R. Balzer, W. Fellows-Mayle, E. De Momi, and C. Riviere. Toward improving safety in neurosurgery with an active handheld instrument. Ann. Biomed. Eng. 46(10):1450–1464, 2018.

    PubMed  PubMed Central  Google Scholar 

  124. Moccia, S., L. S. Mattos, I. Patrini, M. Ruperti, N. Poté, F. Dondero, F. Cauchy, A. Sepulveda, O. Soubrane, E. De Momi, et al.. Computer-assisted liver graft steatosis assessment via learning-based texture analysis. Int. J. Comput. Assist. Radiol. Surg. 13(9):1357–1367, 2018.

    PubMed  Google Scholar 

  125. Moccia, S., E. De Momi, M. Guarnaschelli, M. Savazzi, A. Laborai, L. Guastini, G. Peretti, and L. S. Mattos. Confident texture-based laryngeal tissue classification for early stage diagnosis support. J. Med. Imaging 4(3):034502, 2017.

    Google Scholar 

  126. Moccia, S., E. De Momi, S. El Hadji, and L. S. Mattos. Blood vessel segmentation algorithms–review of methods, datasets and evaluation metrics. Comput. Methods Programs Biomed. 158:71–91, 2018.

    PubMed  Google Scholar 

  127. Moccia, S., V. Penza, G. O. Vanone, E. De Momi, and L. S. Mattos. Automatic workflow for narrow-band laryngeal video stitching,” in 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society:1188–1191, IEEE, New York, 2016.

  128. Moccia, S., G. O. Vanone, E. De Momi, A. Laborai, L. Guastini, G. Peretti, and L. S. Mattos. Learning-based classification of informative laryngoscopic frames. Comput. Methods Programs Biomed. 158:21–30, 2018.

    PubMed  Google Scholar 

  129. Moccia, S., S. J. Wirkert, H. Kenngott, A. S. Vemuri, M. Apitz, B. Mayer, E. De Momi, L. S. Mattos, and L. Maier-Hein. Uncertainty-aware organ classification for surgical data science applications in laparoscopy. IEEE Trans. Biomed. Eng. 65:2649–2659, 2018

    PubMed  Google Scholar 

  130. Mohyeldin, A. and J. B. Elder. Stereotactic biopsy platforms with intraoperative imaging guidance. Neurosurg. Clin. 28(4):465–475, 2017.

    Google Scholar 

  131. Mura, M., S. Parrini, G. Ciuti, V. Ferrari, C. Freschi, M. Ferrari, P. Dario, and A. Menciassi. A computer-assisted robotic platform for vascular procedures exploiting 3D US-based tracking. Comput. Assisted Surg. 21(1):63–79, 2016.

    Google Scholar 

  132. Nadeau, C., H. Ren, A. Krupa, and P. Dupont. Intensity-based visual servoing for instrument and tissue tracking in 3d ultrasound volumes. IEEE Trans. Autom. Sci. Eng. 12(1):367–371, 2015.

    Google Scholar 

  133. Nandy, S., A. Mostafa, P. D. Kumavor, M. Sanders, M. Brewer, and Q. Zhu. Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging. J. Biomed. Opt. 21(10):101402, 2016.

    PubMed  PubMed Central  Google Scholar 

  134. Nguyen, F. T., A. M. Zysk, E. J. Chaney, S. G. Adie, J. G. Kotynek, U. J. Oliphant, F. J. Bellafiore, K. M. Rowland, P. A. Johnson, and S. A. Boppart. Optical coherence tomography: the intraoperative assessment of lymph nodes in breast cancer. IEEE Eng. Med. Biol. Mag. 29(2):63–70, 2010.

    PubMed  PubMed Central  Google Scholar 

  135. Ning, R., X. Tang, and D. Conover. X-ray scatter correction algorithm for cone beam ct imaging. Med. Phys. 31(5):1195–1202, 2004.

    PubMed  Google Scholar 

  136. Nolan, R. M., S. G. Adie, M. Marjanovic, E. J. Chaney, F. A. South, G. L. Monroy, N. D. Shemonski, S. J. Erickson-Bhatt, R. L. Shelton, A. J. Bower, D. G. Simpson, K. A. Cradock, Z. G. Liu, P. S. Ray, and S. A. Boppart. Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer. BMC Cancer 16(1):144, 2016.

    PubMed  PubMed Central  Google Scholar 

  137. Ohayon, S., A. Caravaca-Aguirre, R. Piestun, and J. J. DiCarlo. Minimally invasive multimode optical fiber microendoscope for deep brain fluorescence imaging. Biomed. Opt. Express 9(4):1492–1509, 2018.

    CAS  PubMed  PubMed Central  Google Scholar 

  138. Olmos, R. A. V., S. Vidal-Sicart, and O. E. Nieweg. Technological innovation in the sentinel node procedure: towards 3-d intraoperative imaging. Eur. J. Nucl. Med. Mol. Imaging 37(8):1449–1451, 2010.

    Google Scholar 

  139. Ozkan, E. and A. Eroglu. The utility of intraoperative handheld gamma camera for detection of sentinel lymph nodes in melanoma. Nucl. Med. Mol. Imaging 49(4):318–320, 2015.

    PubMed  PubMed Central  Google Scholar 

  140. Padoy, N., T. Blum, S.-A. Ahmadi, H. Feussner, M.-O. Berger, and N. Navab. Statistical modeling and recognition of surgical workflow. Med. Image Anal. 16(3):632–641, 2012.

    PubMed  Google Scholar 

  141. Papalazarou, C., G. J. Klop, M. T. Milder, J. P. Marijnissen, V. Gupta, B. J. Heijmen, J. J. Nuyttens, and M. S. Hoogeman. Cyberknife with integrated ct-on-rails: System description and first clinical application for pancreas sbrt. Med. Phys. 44(9):4816–4827, 2017.

    PubMed  Google Scholar 

  142. Patete, P., M. Riboldi, M. F. Spadea, G. Catanuto, A. Spano, M. Nava, and G. Baroni. Motion compensation in hand-held laser scanning for surface modeling in plastic and reconstructive surgery. Ann. Biomed. Eng. 37(9):1877–1885, 2009.

    PubMed  Google Scholar 

  143. Pediconi, F., F. Marzocca, B. Cavallo Marincola, and A. Napoli. MRI-guided treatment in the breast. J. Magn. Reson. Imaging 48(6):1479–1488, 2018.

    PubMed  Google Scholar 

  144. Petrover, D., and P. Richette. Treatment of carpal tunnel syndrome: from ultrasonography to ultrasound guided carpal tunnel release. Joint Bone Spine 85(5):545–552, 2018.

    PubMed  Google Scholar 

  145. Pike, R., G. Lu, D. Wang, Z. G. Chen, and B. Fei. A minimum spanning forest-based method for noninvasive cancer detection with hyperspectral imaging.. IEEE Trans. Biomed. Eng. 63(3):653–663, 2016.

    PubMed  Google Scholar 

  146. Pileggi, G., C. Speier, G. C. Sharp, D. Izquierdo Garcia, C. Catana, J. Pursley, F. Amato, J. Seco, and M. F. Spadea. Proton range shift analysis on brain pseudo-ct generated from t1 and t2 mr. Acta Oncol. 57(11):1521–1531, 2018.

    CAS  PubMed  Google Scholar 

  147. Pollard, J. M., Z. Wen, R. Sadagopan, J. Wang, and G. S. Ibbott. The future of image-guided radiotherapy will be MR guided. Br. J. Radiol. 90(1073):20160667, 2017.

    PubMed  PubMed Central  Google Scholar 

  148. Prati, F., L. DiVito, G. Biondi-Zoccai, M. Occhipinti, A. LaManna, C. Tamburino, F. Burzotta. Angiography alone versus angiography plus optical coherence tomography to guide decision-making during percutaneous coronary intervention: the centro per la lotta contro l’infarto-optimisation of percutaneous coronary intervention (CLI-OPCI) study. EuroIntervention 8:823–829, 2012.

    PubMed  Google Scholar 

  149. Prevost, R., M. Salehi, S. Jagoda, N. Kumar, J. Sprung, A. Ladikos, R. Bauer, O. Zettinig, and W. Wein. 3D freehand ultrasound without external tracking using deep learning. Med. Image Anal. 48:187 – 202, 2018.

    PubMed  Google Scholar 

  150. Rabie, A., A. M. Ibrahim, B. T. Lee, and S. J. Lin. Use of intraoperative computed tomography in complex facial fracture reduction and fixation. J. Craniofac. Surg. 22(4):1466–1467, 2011.

    PubMed  Google Scholar 

  151. Rahim, H. M., E. Shlofmitz, A. Gore, E. Hakemi, G. S. Mintz, A. Maehara, A. Jeremias, O. Ben-Yehuda, G. W. Stone, R. A. Shlofmitz, and Z. A. Ali. Ivus- versus oct-guided coronary stent implantation: a comparison of intravascular imaging for stent optimization. Curr. Cardiovasc. Imaging Rep. 11:34, 2018.

    Google Scholar 

  152. Raudaschl, P. F., P. Zaffino, G. C. Sharp, M. F. Spadea, A. Chen, B. M. Dawant, T. Albrecht, T. Gass, C. Langguth, M. Lüthi, F. Jung, O. Knapp, S. Wesarg, R. Mannion-Haworth, M. Bowes, A. Ashman, G. Guillard, A. Brett, G. Vincent, M. Orbes-Arteaga, D. Cardenas-Pena, G. Castellanos-Dominguez, N. Aghdasi, Y. Li, A. Berens, K. Moe, B. Hannaford, R. Schubert, and K. D. Fritscher. Evaluation of segmentation methods on head and neck ct: auto-segmentation challenge 2015. Med. Phys. 44(5):2020–2036, 2017.

    PubMed  Google Scholar 

  153. Ray, R., D. E. Barañano, J. A. Fortun, B. J. Schwent, B. E. Cribbs, C. S. Bergstrom, G. B. Hubbard III, and S. K. Srivastava. Intraoperative microscope-mounted spectral domain optical coherence tomography for evaluation of retinal anatomy during macular surgery. Ophthalmology 118(11):2212–2217, 2011.

    PubMed  Google Scholar 

  154. Ray, A., X. Wang, Y.-E. K. Lee, H. J. Hah, G. Kim, T. Chen, D. A. Orringer, O. Sagher, X. Liu, and R. Kopelman. Targeted blue nanoparticles as photoacoustic contrast agent for brain tumor delineation. Nano Research 4(11):1163–1173, 2011.

    PubMed  PubMed Central  Google Scholar 

  155. Reder, N. P., S. Kang, A. K. Glaser, Q. Yang, M. A. Wall, S. H. Javid, S. M. Dintzis, and J. T. Liu. Raman-encoded molecular imaging with topically applied SERS nanoparticles for intraoperative guidance of lumpectomy. Cancer Res. 77(16):4506–4516, 2017.

    PubMed  PubMed Central  Google Scholar 

  156. Reiml, S., T. Kurzendorfer, D. Toth, P. Mountney, S. Steidl, A. Brost, and A. Maier. Automatic vertebrae segmentation in fluoroscopic images for electrophysiology,” in 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), Springer, Cham 2017.

  157. Riva, M., C. Hennersperger, F. Milletari, A. Katouzian, F. Pessina, B. Gutierrez-Becker, A. Castellano, N. Navab, and L. Bello. 3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation. Int. J. Comput. Assist. Radiol. Surg. 12:1711–1725, 2017.

    PubMed  Google Scholar 

  158. Roessler, K., A. Hofmann, B. Sommer, P. Grummich, R. Coras, B. S. Kasper, H. M. Hamer, I. Blumcke, H. Stefan, C. Nimsky, and M. Buchfelder. Resective surgery for medically refractory epilepsy using intraoperative MRI and functional neuronavigation: the erlangen experience of 415 patients. Neurosurg. Focus 40(3):E15, 2016.

    PubMed  Google Scholar 

  159. Sanghvi, N. T., R. Bihrle, and F. J. Fry. Focussed ultrasound tissue treatment method. US Patent 5,676,692, 1997

  160. Santos, I. P., E. M. Barroso, T. C. B. Schut, P. J. Caspers, C. G. van Lanschot, D.-H. Choi, M. F. van der Kamp, R. W. Smits, R. van Doorn, R. M. Verdijk, V. Noordhoek Hegt, J. von der Thüsen, C. H. M. van Deurzen, L. B. Koppert, J. L. H. van Leenders, P. C. Ewing-Graham, H. C. van Doorn, C. M. F. Dirven, M. B. Busstra, J. Hardillo, A. Sewnaik, I. ten Hove, H. Mast, D. A. Monserez, C. Meeuwis, T. Nijsten, E. B. Wolvius, R. J. Baatenburg de Jong, G. J. Puppels, and S. Koljenovic. Raman spectroscopy for cancer detection and cancer surgery guidance: translation to the clinics. Analyst 142(17):3025–3047, 2017.

    CAS  PubMed  Google Scholar 

  161. Saso, S., N. T. Clancy, B. P. Jones, T. Bracewell-Milnes, M. Al-Memar, E. M. Cannon, S. Ahluwalia, J. Yazbek, M.-Y. Thum, T. Bourne, D. S. Elson, J. R. Smith, and S. Ghaem-Maghami. Use of biomedical photonics in gynecological surgery: a uterine transplantation model. Fut. Sci. 4(4):FSO286, 2018.

    CAS  Google Scholar 

  162. Saw, C. B., C. Gillette, C. A. Peters, and L. Koutcher. Clinical implementation of radiosurgery using the helical tomotherapy unit. Med. Dosim. 43(3):284–290, 2018.

    PubMed  Google Scholar 

  163. Schafer, S., Y. Otake, A. Uneri, D. J. Mirota, S. Nithiananthan, J. W. Stayman, W. Zbijewski, G. Kleinszig, R. Graumann, M. Sussman, and J. H. Siewerdsen. High-performance C-arm cone-beam CT guidance of thoracic surgery. Int. Soc. Opt. Photon. 8316:831611 (2012)

    Google Scholar 

  164. Schichor, C., N. Terpolilli, J. Thorsteinsdottir, and J.-C. Tonn. Intraoperative computed tomography in cranial neurosurgery. Neurosurg. Clin. 28(4):595–602, 2017.

    Google Scholar 

  165. Schwartz, J. G., A. M. Neubauer, T. E. Fagan, N. J. Noordhoek, M. Grass, and J. D. Carroll. Potential role of three-dimensional rotational angiography and c-arm ct for valvular repair and implantation. Int. J. Cardiovasc. Imaging 27(8):1205–1222, 2011.

    PubMed  Google Scholar 

  166. Seco, J., M. Oumano, N. Depauw, M. F. Dias, R. P. Teixeira, and M. F. Spadea. Characterizing the modulation transfer function (mtf) of proton/carbon radiography using Monte Carlo simulations. Med. Phys. 40(9):91717, 2013

    Google Scholar 

  167. Seco, J. and M. F. Spadea. Imaging in particle therapy: state of the art and future perspective. Acta Oncol. 54(9):1254–1258, 2015.

    PubMed  Google Scholar 

  168. Sequeiros, R. B., J.-J. Sinikumpu, R. Ojala, J. Järvinen, and J. Fritz. Pediatric musculoskeletal interventional mri. Top. Magn. Reson. Imaging 27(1):39–44, 2018.

    PubMed  Google Scholar 

  169. Sharma, M. and M. Deogaonkar. Accuracy and safety of targeting using intraoperative “O-arm” during placement of deep brain stimulation electrodes without electrophysiological recordings. J. Clin. Neurosci. 27:80–86, 2016.

    PubMed  Google Scholar 

  170. Shaye, D. A., T. T. Tollefson, and E. B. Strong. Use of intraoperative computed tomography for maxillofacial reconstructive surgery. JAMA Facial Plast. Surg. 17(2):113–119, 2015.

    PubMed  Google Scholar 

  171. Siebelmann, S., C. Cursiefen, A. Lappas, and T. Dietlein. Intraoperative optical coherence tomography enables noncontact imaging during canaloplasty. J. Glaucoma 25(2):236–238, 2016.

    PubMed  Google Scholar 

  172. Simpfendörfer, T., C. Gasch, G. Hatiboglu, M. Müller, L. Maier-Hein, M. Hohenfellner, and D. Teber. Intraoperative computed tomography imaging for navigated laparoscopic renal surgery: first clinical experience. J. Endourol. 30(10):1105–1111, 2016.

    PubMed  Google Scholar 

  173. Sommerey, S. , N. Al Arabi, R. Ladurner, C. Chiapponi, H. Stepp, K. K. Hallfeldt, and J. K. Gallwas. Intraoperative optical coherence tomography imaging to identify parathyroid glands. Surg. Endosc. 29(9):2698–2704, 2015.

    PubMed  Google Scholar 

  174. Song, S., J. Xu, and R. K. Wang. Long-range and wide field of view optical coherence tomography for in vivo 3D imaging of large volume object based on akinetic programmable swept source. Biomed. Opt. Express 7(11):4734–4748, 2016.

    PubMed  PubMed Central  Google Scholar 

  175. Spadea, M. F., A. Fassi, P. Zaffino, M. Riboldi, G. Baroni, N. Depauw, and J. Seco. Contrast-enhanced proton radiography for patient set-up by using x-ray ct prior knowledge. Int. J. Radiat. Oncol. Biol. Phys. 90(3):628–636, 2014.

    PubMed  Google Scholar 

  176. Spadea, M. F., G. Pileggi, P. Zaffino, P. Salome, C. Catana, D. Izquierdo-Garcia, F. Amato, and J. Seco. Deep convolution neural network (dcnn) multiplane approach to synthetic ct generation from mr images–application in brain proton therapy. Int. J. Radiat. Oncol. Biol. Phys. 105(3):495–503, 2019.

    CAS  PubMed  Google Scholar 

  177. Spadea, M. F., B. Tagaste, M. Riboldi, E. Preve, D. Alterio, G. Piperno, C. Garibaldi, R. Orecchia, A. Pedotti, and G. Baroni. Intra-fraction setup variability: IR optical localization vs. X-ray imaging in a hypofractionated patient population. Radiat. Oncol. 6(1):38, 2011.

    PubMed  PubMed Central  Google Scholar 

  178. Spadea, M. F., J. Verburg, G. Baroni, and J. Seco. Dosimetric assessment of a novel metal artifact reduction method in ct images. J. Appl. Clin. Med. Phys. 14(1):299–304, 2013.

    PubMed Central  Google Scholar 

  179. Suetens, P. Fundamentals of Medical Imaging. Cambridge: Cambridge University Press, 2002.

    Google Scholar 

  180. Sullivan, J. P., B. A. Warme, and B. R. Wolf. Use of an o-arm intraoperative computed tomography scanner for closed reduction of posterior sternoclavicular dislocations. J. Shoulder Elbow Surg. 21(3):e17–e20, 2012.

    PubMed  Google Scholar 

  181. Suzuki, T., Y. Sakurai, K. Yoshimitsu, K. Nambu, Y. Muragaki, and H. Iseki. Intraoperative multichannel audio-visual information recording and automatic surgical phase and incident detection,” in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE:1190–1193, IEEE, New Yok, 2010.

  182. Tamadazte, B., A. Agustinos, P. Cinquin, G. Fiard, and S. Voros. Multi-view vision system for laparoscopy surgery. Int. J. Comput. Assist. Radiol. Surg. 10(2):195–203, 2015.

    PubMed  Google Scholar 

  183. Tappeiner, E., S. Pröll, M. Hönig, P. F. Raudaschl, P. Zaffino, M. F. Spadea, G. C. Sharp, R. Schubert, and K. Fritscher. Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach. Int. J. Comput. Assist. Radiol. Surg. 14(5):745–754, 2019.

    PubMed  Google Scholar 

  184. Taruttis, A., E. Herzog, D. Razansky, and V. Ntziachristos. Real-time imaging of cardiovascular dynamics and circulating gold nanorods with multispectral optoacoustic tomography. Opt. Express 18(19):19592–19602, 2010.

    CAS  PubMed  Google Scholar 

  185. Taruttis, A. and V. Ntziachristos. Advances in real-time multispectral optoacoustic imaging and its applications. Nat. Photonics 9(4):219, 2015.

    CAS  Google Scholar 

  186. Tempany, C. M., J. Jayender, T. Kapur, R. Bueno, A. Golby, N. Agar, and F. A. Jolesz. Multimodal imaging for improved diagnosis and treatment of cancers. Cancer 121(6):817–827, 2015.

    PubMed  Google Scholar 

  187. Thatcher, J. E., W. Li, Y. Rodriguez-Vaqueiro, J. J. Squiers, W. Mo, Y. Lu, K. D. Plant, E. Sellke, D. R. King, W. Fan, J. A. Martinez-Lorenzo, and J. M. DiMaio. Multispectral and photoplethysmography optical imaging techniques identify important tissue characteristics in an animal model of tangential burn excision. J. Burn Care Res. 37(1):38–52, 2016.

    PubMed  Google Scholar 

  188. Thatcher, J. E., J. J. Squiers, S. C. Kanick, D. R. King, Y. Lu, Y. Wang, R. Mohan, E. W. Sellke, and J. M. DiMaio. Imaging techniques for clinical burn assessment with a focus on multispectral imaging. Adv. Wound Care 5(8):360–378, 2016.

    Google Scholar 

  189. Thomas, G., T.-Q. Nguyen, I. Pence, B. Caldwell, M. O’Connor, J. Giltnane, M. Sanders, A. Grau, I. Meszoely, M. Hooks, M. C. Kelley, and A. Mahadevan-Jansen. Evaluating feasibility of an automated 3-dimensional scanner using Raman spectroscopy for intraoperative breast margin assessment. Sci. Rep. 7(1):13548, 2017.

    CAS  PubMed  PubMed Central  Google Scholar 

  190. Thummerer, A., P. Zaffino, A. Meijers, G. G. Marmitt, J. Seco, R. J. Steenbakkers, J. A. Langendijk, S. Both, M. F. Spadea, and A.-C. Knopf. Comparison of cbct based synthetic ct methods suitable for proton dose calculations in adaptive proton therapy. Phys. Med. Biol. 65(9):095002, 2020.

    PubMed  Google Scholar 

  191. Tipirneni, K., E. Rosenthal, L. Moore, A. Haskins, N. Udayakumar, A. Jani, W. Carroll, A. Morlandt, M. Bogyo, J. Rao, et al.. Fluorescence imaging for cancer screening and surveillance. Mol. Imag. Biol. 19(5):645–655, 2017.

    CAS  Google Scholar 

  192. Tousignant, C., M. Desmet, R. Bowry, A. M. Harrington, J. D. Cruz, and C. D. Mazer. Speckle tracking for the intraoperative assessment of right ventricular function: a feasibility study. J. Cardiothorac. Vasc. Anesth. 24(2):275–279, 2010.

    PubMed  Google Scholar 

  193. Tummers, W. S., S. E. Miller, N. T. Teraphongphom, A. Gomez, I. Steinberg, D. M. Huland, S. Hong, S.-R. Kothapalli, A. Hasan, R. Ertsey, et al.. Intraoperative pancreatic cancer detection using tumor-specific multimodality molecular imaging. Ann. Surg. Oncol. 25(7):1880–1888, 2018.

    PubMed  PubMed Central  Google Scholar 

  194. Tzifa, A., T. Schaeffter, and R. Razavi. MR imaging-guided cardiovascular interventions in young children. Magn. Reson. Imaging Clin. 20(1):117–128, 2012.

    Google Scholar 

  195. Uh, J., T. E. Merchant, Y. Li, X. Li, and C. Hua. Mri-based treatment planning with pseudo ct generated through atlas registration. Med. Phys. 41(5):051711, 2014.

    PubMed  PubMed Central  Google Scholar 

  196. Unger, J., C. Hebisch, J. E. Phipps, J. L. Lagarto, H. Kim, M. A. Darrow, R. J. Bold, and L. Marcu. Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning. Biomed. Opt. Express 11(3):1216, 2020.

    PubMed  PubMed Central  Google Scholar 

  197. Van Dam, G. M. , G. Themelis, L. M. Crane, N. J. Harlaar, R. G. Pleijhuis, W. Kelder, A. Sarantopoulos, J. S. De Jong, H. J. Arts, A. G. Van Der Zee, J. Bart, P. S. Low, and V. Ntziachristos. Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-\(\alpha\) targeting: first in-human results. Nat. Med. 17(10):1315, 2011.

    PubMed  Google Scholar 

  198. van den Berg, N. S., T. Buckle, G. H. KleinJan, H. G. van der Poel, and F. W. van Leeuwen. Multispectral fluorescence imaging during robot-assisted laparoscopic sentinel node biopsy: a first step towards a fluorescence–based anatomic roadmap. Eur. Urol. 72(1):110–117, 2017.

    PubMed  Google Scholar 

  199. van den Berg, P., K. Daoudi, and W. Steenbergen. Review of photoacoustic flow imaging: its current state and its promises. Photoacoustics 3(3):89–99, 2015.

    PubMed  PubMed Central  Google Scholar 

  200. Vermeeren, L., W. Meinhardt, A. Bex, H. G. van der Poel, W. V. Vogel, C. A. Hoefnagel, S. Horenblas, and R. A. V. Olmos. Paraaortic sentinel lymph nodes: toward optimal detection and intraoperative localization using spect/ct and intraoperative real-time imaging. J. Nucl. Med. 51(3):376–382, 2010.

    PubMed  Google Scholar 

  201. Vermeeren, L., R. A. V. Olmos, W. M. C. Klop, A. J. Balm, and M. W. van den Brekel. A portable \(\gamma\)-camera for intraoperative detection of sentinel nodes in the head and neck region. J. Nucl. Med. 51(5):700–703, 2010.

    PubMed  Google Scholar 

  202. Vermeeren, L., R. A. V. Olmos, W. Meinhardt, and S. Horenblas. Intraoperative imaging for sentinel node identification in prostate carcinoma: its use in combination with other techniques. J. Nucl. Med. 52(5):741–744, 2011.

    PubMed  Google Scholar 

  203. Viergever, M. A., J. A. Maintz, S. Klein, K. Murphy, M. Staring, and J. P. Pluim, A survey of medical image registration. Med. Image Anal. 2:1–36, 2016.

    Google Scholar 

  204. Walsh, E. M., D. Cole, K. E. Tipirneni, K. I. Bland, N. Udayakumar, B. B. Kasten, S. L. Bevans, B. M. McGrew, J. J. Kain, Q. T. Nguyen, et al.. Fluorescence imaging of nerves during surgery. Ann. Surg. 270(1):69–76, 2019.

    PubMed  Google Scholar 

  205. Wang, Y. W., S. Kang, A. Khan, P. Q. Bao, and J. T. Liu. In vivo multiplexed molecular imaging of esophageal cancer via spectral endoscopy of topically applied SERS nanoparticles. Biomed. Opt. Express 6(10):3714–3723, 2015.

    CAS  PubMed  PubMed Central  Google Scholar 

  206. Wang, Y., S. Kang, A. Khan, G. Ruttner, S. Y. Leigh, M. Murray, S. Abeytunge, G. Peterson, M. Rajadhyaksha, S. Dintzis, S. Javid, and J. T. Liu. Quantitative molecular phenotyping with topically applied sers nanoparticles for intraoperative guidance of breast cancer lumpectomy. Sci. Rep. 6:21242, 2016.

    CAS  PubMed  PubMed Central  Google Scholar 

  207. Warsi, N. M., O. Lasry, A. Farah, C. Saint-Martin, J. L. Montes, J. Atkinson, J.-P. Farmer, and R. W. Dudley. 3-T intraoperative MRI (iMRI) for pediatric epilepsy surgery. Child’s Nervous Syst. 32(12):2415–2422, 2016.

    Google Scholar 

  208. Wegelin, O., H. H. van Melick, L. Hooft, J. R. Bosch, H. B. Reitsma, J. O. Barentsz, and D. M. Somford. Comparing three different techniques for magnetic resonance imaging-targeted prostate biopsies: a systematic review of in-bore versus magnetic resonance imaging-transrectal ultrasound fusion versus cognitive registration. is there a preferred technique?. Eur. Urol. 71(4):517–531, 2017.

    PubMed  Google Scholar 

  209. Weyers, B. W., M. Marsden, T. Sun, J. Bec, A. F. Bewley, R. F. Gandour-Edwards, M. G. Moore, D. G. Farwell, and L. Marcu. Fluorescence lifetime imaging for intraoperative cancer delineation in transoral robotic surgery. Transl. Biophoton. 1(1–2):e201900017, 2019.

    Google Scholar 

  210. Wieser, W. , B. R. Biedermann, T. Klein, C. M. Eigenwillig, and R. Huber. Multi-megahertz OCT: High quality 3D imaging at 20 million A-scans and 4.5 GVoxel per second. Opt. Express 18(14):14685–14704, 2010.

    PubMed  Google Scholar 

  211. Wild, E., D. Teber, D. Schmid, T. Simpfendörfer, M. Müller, A.-C. Baranski, H. Kenngott, K. Kopka, and L. Maier-Hein. Robust augmented reality guidance with fluorescent markers in laparoscopic surgery. Int. J. Comput. Assist. Radiol. Surg. 11(6):899–907, 2016.

    PubMed  Google Scholar 

  212. Wirkert, S. J., N. T. Clancy, D. Stoyanov, S. Arya, G. B. Hanna, H.-P. Schlemmer, P. Sauer, D. S. Elson, and L. Maier-Hein. Endoscopic sheffield index for unsupervised in vivo spectral band selection,” in: S. J. Wirkert, N. T. Clancy (eds) International Workshop on Computer-Assisted and Robotic Endoscopy:110–120, Springer, Cham (2014)

    Google Scholar 

  213. Wirkert, S. J., H. Kenngott, B. Mayer, P. Mietkowski, M. Wagner, P. Sauer, N. T. Clancy, D. S. Elson, and L. Maier-Hein. Robust near real-time estimation of physiological parameters from megapixel multispectral images with inverse Monte Carlo and random forest regression. Int. J. Comput. Assist. Radiol. Surg. 11(6):909–917, 2016.

    PubMed  PubMed Central  Google Scholar 

  214. Wirkert, S. J., A. S. Vemuri, H. G. Kenngott, S. Moccia, M. Götz, B. F. Mayer, K. H. Maier-Hein, D. S. Elson, and L. Maier-Hein. Physiological parameter estimation from multispectral images unleashed,” in International Conference on Medical Image Computing and Computer-Assisted Intervention:134–141, Springer, Cham (2017).

  215. Wong, W. K., Y. Matsuwaki, K. Omura, and H. Moriyama. Role of intraoperative ct-updates during image-guided endoscopic sinus surgery for sinonasal fibro-osseous lesions. Auris Nasus Larynx 38(5):628–631, 2011.

    PubMed  Google Scholar 

  216. Yang, J.-M., K. Maslov, H.-C. Yang, Q. Zhou, K. K. Shung, and L. V. Wang. Photoacoustic endoscopy. Opt. Lett. 34(10):1591–1593, 2009.

    PubMed  PubMed Central  Google Scholar 

  217. Yao, J. and L. V. Wang. Photoacoustic brain imaging: from microscopic to macroscopic scales. Neurophotonics 1(1):011003, 2014.

    PubMed Central  Google Scholar 

  218. Yun, S.-H., G. J. Tearney, J. F. de Boer, N. Iftimia, and B. E. Bouma. High-speed optical frequency-domain imaging. Opt. express 11(22):2953–2963, 2003.

    CAS  PubMed  PubMed Central  Google Scholar 

  219. Zaffino, P., D. Ciardo, G. Piperno, L. Travaini, S. Comi, A. Ferrari, D. Alterio, B. Jereczek-Fossa, R. Orecchia, G. Baroni, and M. F. Spadea. Radiotherapy of Hodgkin and non-Hodgkin lymphoma: A nonrigid image-based registration method for automatic localization of prechemotherapy gross tumor volume. Technol. Cancer Res. Treat. 15(2):355–364, 2016.

    CAS  PubMed  Google Scholar 

  220. Zaffino, P., G. Pernelle, A. Mastmeyer, A. Mehrtash, H. Zhang, R. Kikinis, T. Kapur, and M. F. Spadea. Fully automatic catheter segmentation in mri with 3d convolutional neural networks: application to mri-guided gynecologic brachytherapy. Phys. Med. Biol. 64(16):165008, 2019.

    PubMed  Google Scholar 

  221. Zelefsky, M. J., M. Worman, G. N. Cohen, X. Pei, M. Kollmeier, J. Yamada, B. Cox, Z. Zhang, E. Bieniek, L. Dauer, and M. Zaider. Real-time intraoperative computed tomography assessment of quality of permanent interstitial seed implantation for prostate cancer. Urology 76(5):1138–1142, 2010.

    PubMed  PubMed Central  Google Scholar 

  222. Zhu, L., Y. Xie, J. Wang, and L. Xing. Scatter correction for cone-beam ct in radiation therapy. Med. Phys. 36(6Part1):2258–2268, 2009.

    PubMed  PubMed Central  Google Scholar 

  223. Zuzak, K. J., R. P. Francis, E. F. Wehner, M. Litorja, J. A. Cadeddu, and E. H. Livingston. Active DLP hyperspectral illumination: a noninvasive, in vivo, system characterization visualizing tissue oxygenation at near video rates. Anal. Chem. 83(19):7424–7430, 2011.

    CAS  PubMed  Google Scholar 

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  1. Paolo Zaffino and Sara Moccia have equally contributed to this paper.

Authors and Affiliations

  1. Department of Experimental and Clinical Medicine, Universitá della Magna Graecia, Catanzaro, Italy

    Paolo Zaffino & Maria Francesca Spadea

  2. Department of Information Engineering (DII), Universitá Politecnica delle Marche, via Brecce Bianche, 12, 60131, Ancona, AN, Italy

    Sara Moccia

  3. Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milano, MI, Italy

    Elena De Momi

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  1. Paolo Zaffino
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Zaffino, P., Moccia, S., De Momi, E. et al. A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future. Ann Biomed Eng 48, 2171–2191 (2020). https://doi.org/10.1007/s10439-020-02553-6

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