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Auxiliary Tools for Enhanced Depth Perception in Vascular Structures

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Biomedical Visualisation

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1138))

Abstract

This chapter discusses the concept of Auxiliary Tools in depth perception. Four recent techniques are considered, that apply the concept in the domain of liver vasculature visualization. While an improvement is evident, the evaluations and conducted studies are found to be biased and not general enough to provide a convincing assessment. The chapter provides background information about human visual perception and a brief history on vascular visualization. Then four state-of-the-art methods are discussed. Finally, a comparative discussion points out objectives for future follow-up work.

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References

  • Alpers J, Hansen C, Ringe K et al (2017) Ct-based navigation guidance for liver tumor ablation. In: Proceedings of the VCBM

    Google Scholar 

  • Borgo R, Kehrer J, Chung DH et al (2013) Glyph-based visualization: foundations, design guidelines, techniques and applications. In: Eurographics (STARs), pp 39–63

    Google Scholar 

  • Bruckner S, Gröller E (2007) Enhancing depth-perception with flexible volumetric halos. IEEE Trans Vis Comput Graph 13(6):1344–1351

    Article  Google Scholar 

  • Gerig G, Koller T, Székely G et al (1993) Symbolic description of 3-d structures applied to cerebral vessel tree obtained from mr angiography volume data. In: Biennial international conference on information processing in medical imaging, Springer, pp 94–111

    Google Scholar 

  • Glueck M, Crane K, Anderson S et al (2009) Multiscale 3d reference visualization. In: Proceedings of the 2009 symposium on interactive 3D graphics and games, ACM, pp 225–232

    Google Scholar 

  • Hahn HK, Preim B, Selle D et al (2001) Visualization and interaction techniques for the exploration of vascular structures. In: Visualization, 2001. VIS’01. Proceedings, IEEE, pp 395–578

    Google Scholar 

  • Hansen C, Zidowitz S, Preim B et al (2014) Impact of model-based risk analysis for liver surgery planning. Int J Comput Assist Radiol Surg 9(3):473–480

    Article  CAS  Google Scholar 

  • Healey C, Enns J (2012) Attention and visual memory in visualization and computer graphics. IEEE Trans Vis Comput Graph 18(7):1170–1188

    Article  Google Scholar 

  • Hernández-Hoyos M, Anwander A, Orkisz M et al (2000) A deformable vessel model with single point initialization for segmentation, quantification, and visualization of blood vessels in 3d mra. In: International conference on medical image computing and computer-assisted intervention, Springer, pp 735–745

    Google Scholar 

  • Hubona GS, Wheeler PN, Shirah GW et al (1999) The relative contributions of stereo, lighting, and background scenes in promoting 3D depth visualization. ACM Trans Comput Hum Interact 6:214–242

    Article  Google Scholar 

  • Kersten M, Stewart J, Troje N et al (2006) Enhancing depth perception in translucent volumes. IEEE Trans Vis Comput Graph 12(5):1117–1124

    Article  Google Scholar 

  • Kersten-Oertel M, Chen SJ, Collins DL (2014) An evaluation of depth enhancing perceptual cues for vascular volume visualization in neurosurgery. IEEE Trans Vis Comput Graph 20(3):391–403

    Article  Google Scholar 

  • Kreiser J, Hermosilla P, Ropinski T (2018) Void space surfaces to convey depth in vessel visualizations. ArXiv e-prints 1806.07729

    Google Scholar 

  • Lawonn K, Luz M, Preim B et al (2015) Illustrative visualization of vascular models for static 2d representations. In: Medical Image Computing and Computer- Assisted Intervention (MICCAI), pp 399–406

    Google Scholar 

  • Lawonn K, Luz M, Hansen C (2017) Improving spatial perception of vascular models using supporting anchors and illustrative visualization. Comput Graph 63:37–49

    Article  Google Scholar 

  • Lichtenberg N, Hansen C, Lawonn K (2017) Concentric circle glyphs for enhanced depth-judgment in vascular models. In: Proceedings of the VCBM

    Google Scholar 

  • Meuschke M, SMIT N, Lichtenberg N et al (2018) Automatic generation of web-based user studies to evaluate depth perception in vascular surface visualizations. In: Proceedings of the VCBM

    Google Scholar 

  • Preim B, Baer A, Cunningham D et al (2016) A survey of perceptually motivated 3D visualization of medical image data. Comput Graph Forum 35(3):501–525

    Article  Google Scholar 

  • Preim B, Ropinski T, Isenberg P (2018) A critical analysis of the evaluation practice in medical visualization. In: Eurographics workshop on visual computing for biology and medicine. The Eurographics Association

    Google Scholar 

  • Ritter F, Hansen C, Dicken V et al (2006) Real-time illustration of vascular structures. IEEE Transact Vis Comput Graph 12(5):877–884

    Article  Google Scholar 

  • Rodrigues JF, Traina AJ, de Oliveira MCF et al (2006) Reviewing data visualization: an analytical taxonomical study. In: Tenth international conference on information visualisation (IV’06), IEEE, pp 713–720

    Google Scholar 

  • Ropinski T, Steinicke F, Hinrichs K (2006) Visually supporting depth perception in angiography imaging. In: Smart graphics, lecture notes in computer science, vol 4073. Springer, Berlin/Heidelberg, pp 93–104

    Google Scholar 

  • Ropinski T, Oeltze S, Preim B (2011) Survey of glyph-based visualization techniques for spatial multivariate medical data. Comput Graph 35(2):392–401

    Article  Google Scholar 

  • Saalfeld P, Luz M, Berg P et al (2018) Guidelines for quantitative evaluation of medical visualizations on the example of 3d aneurysm surface comparisons. In: Computer graphics forum, Wiley online library, vol 37, pp 226–238

    Article  Google Scholar 

  • Shepard D (1968) A two-dimensional interpolation function for irregularly-spaced data. In: Proceedings of the 1968 23rd ACM national conference, ACM, pp 517–524

    Google Scholar 

  • Steenblik RA (1987) The chromostereoscopic process: a novel single image stereoscopic process. In: Proceedings of the SPIE, vol 0761, pp 27–34

    Google Scholar 

  • Swan JE, Singh G, Ellis SR (2015) Matching and reaching depth judgments with real and augmented reality targets. IEEE Trans Vis Comput Graph 21(11):1289–1298

    Article  Google Scholar 

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Correspondence to Kai Lawonn .

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Lichtenberg, N., Lawonn, K. (2019). Auxiliary Tools for Enhanced Depth Perception in Vascular Structures. In: Rea, P. (eds) Biomedical Visualisation . Advances in Experimental Medicine and Biology, vol 1138. Springer, Cham. https://doi.org/10.1007/978-3-030-14227-8_8

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