Abstract
We introduce a novel minimally-interactive watershed algorithm that needs no initial parameterization, but lets the user refine the automatic segmentation close to real-time. In contrast to previous proposals, our algorithm encapsulates all time consuming calculation in a processing step executed only once. Thereby, a hierarchical subdivision of the incoming image data is generated. This subdivision serves as a basis for computing automatic segmentation results according to a given multi-dimensional classification scheme as well as for interactive refinement according to local markers. We have successfully applied our algorithm to efficiently removing bone structures from computed tomography angiography data, which is among the very challenging segmentation problems in medical image analysis.
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References
Alyassin, A.M., Avinash, G.B.: Semiautomatic bone removal technique from CT angiography data. Med Imaging. In: Proc. SPIE 2005, vol. 4322, pp. 1273–1283 (2001)
Digabel, H., Lantuèjoul, C.: Iterative algorithms. In: Chermant, J.L. (ed.) Proc. 2nd European Symp. Quantitative Analysis of Micro-structures in Material Science, Biology and Medicine, pp. 85–99 (1978)
Fiebich, M., Straus, C.M., Sehgal, V., Renger, B.C., Doi, K., Hoffmann, K.R.: Automatic bone segmentation technique for CT angiographic studies. J. Comput. Assist. Tomogr. 23(1), 155–161 (1999)
Grau, V., Mewes, A.U.J., Alcañiz, M., Kikinis, R., Warfield, S.K.: Improved watershed transform for medical image segmentation using prior information. IEEE Trans. Med. Imaging 23(4), 447–458 (2004)
Hahn, H.K.: Morphological Volumetry Theory, Concepts, and Application to Quantitative Medical Imaging. Ph.D. thesis, University of Bremen (2005)
Hahn, H.K., Peitgen, H.-O.: The skull stripping problem in MRI solved by a single 3D watershed transform. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 134–143. Springer, Heidelberg (2000)
Hahn, H.K., Peitgen, H.-O.: IWT—Interactive Watershed Transform: A hierarchical method for efficient interactive and automated segmentation of multidimensional grayscale images. In: Med. Imaging, Proc. SPIE, vol. 5032, pp. 643–653 (2003)
Kang, Y., Engelke, K., Kalender, W.A.: A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data. IEEE Trans. Med. Imaging 22(5), 586–598 (2003)
Moore, E.A., Grieve, J.P., Jäger, H.R.: Robust processing of intracranial CT angiograms for 3D volume rendering. Eur. J. Radiol. 11(1), 137–141 (2001)
Mullick, R., Avila, R., Knoplioch, J., Mallya, Y., Platt, J., Senzig, R.: Automatic bone removal for abdomen CTA: A clinical review. In: Proc. RSNA (2002)
Raman, R., Raman, B., Hundt, W., Stucker, D., Napel, S., Rubin, G.D.: Improved speed of bone removal in CT angiography (CTA) using automated targeted morphological separation: Method and evaluation in CTA of lower extremity occlusive disease (LEOD). Radiology 225(P), 647 (2002)
Roerdink, J.B.T.M., Meijster, A.: The watershed transform: Definitions, algorithms, and parallelization strategies. Fundamenta Informaticae 41, 187–228 (2000)
Suryanaranayanan, S., Mullick, R., Mallya, Y., Wood, C., McCullough, C., Thielen, K.: Automatic bone removal for head CTA: A preliminary review. In: Proc. RSNA (2003)
van Straten, M., Venema, H.W., Streekstra, G.J., den Heeten, G.J., Majoie, C.B.L.M.: Removal of bone in CT angiography of the cervical arteries by piecewise matched mask bone elimination. Medical Physics 31 (10), 2924–2933 (2004)
Vincent, L., Soille, P.: Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. Pattern Analysis Machine Intel 13(6), 583–598 (1991)
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Hahn, H.K., Wenzel, M.T., Konrad-Verse, O., Peitgen, HO. (2006). A Minimally-Interactive Watershed Algorithm Designed for Efficient CTA Bone Removal. In: Beichel, R.R., Sonka, M. (eds) Computer Vision Approaches to Medical Image Analysis. CVAMIA 2006. Lecture Notes in Computer Science, vol 4241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11889762_16
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DOI: https://doi.org/10.1007/11889762_16
Publisher Name: Springer, Berlin, Heidelberg
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