Abstract
We present a fully automatic 3D segmentation method for the left ventricle (LV) in human myocardial perfusion SPECT data. This model-based approach consists of 3 phases: 1. finding the LV in the dataset, 2. extracting its approximate shape and 3. segmenting its exact contour.
Finding of the LV is done by flexible pattern matching, whereas segmentation is achieved by registering an anatomical model to the functional data. This model is a new kind of stable 3D mass spring model using direction-weighted 3D contour sensors.
Our approach is much faster than manual segmention, which is standard in this application up to now. By testing it on 41 LV SPECT datasets of mostly pathological data, we could show, that it is very robust and its results are comparable with those made by human experts.
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Fernandez-Maloigne, C., Rakotobe, R.H., Langevin, F., Fauchet, M.: 3D segmentation and visualization of cardiac SPECT studies. In: 28th AIPR Workshop. Proceedings of SPIE, vol. 3905, pp. 222–231 (2000)
Pohle, R., Wegner, M., Rink, K., Tönnies, K., Celler, A., Blinder, S.: Segmentation of the left ventricle in 4D-dSPECT data using free form deformation of super quadrics. In: Medical Imaging: Image Processing. Proceedings of SPIE, vol. 5370, pp. 1388–1394 (2004)
Bardinet, E., Cohen, L.D., Ayache, N.: Tracking and motion analysis of the left ventricle with deformable superquadrics. Medical Image Analysis 1, 129–149 (1996)
Gould, P.L.: Introduction to Linear Elasticity. Springer, Heidelberg (1994)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. IJCV 1, 321–331 (1988)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models - their training and application. CVIU 61, 38–59 (1995)
Dornheim, L., Tönnies, K.D., Dornheim, J.: Stable dynamic 3D shape models. In: ICIP (2005)
Dornheim, L., Tönnies, K.D.: Automatische Generierung dynamischer 3D-Modelle zur Segmentierung des linken Ventrikels in 3D-SPECT-Daten. In: Bildverarbeitung für die Medizin (2005)
Kohonen, T.: Self-Organization and Associative Memory. Springer, Heidelberg (1987)
Dornheim, L.: Generierung und Dynamik physikalisch basierter 3D-Modelle zur Segmentierung des linken Ventrikels in SPECT-Daten. Diplomarbeit, Fakultät für Informatik, Otto-von-Guericke-Universität Magdeburg (2005)
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Dornheim, L., Tönnies, K.D., Dixon, K. (2005). Automatic Segmentation of the Left Ventricle in 3D SPECT Data by Registration with a Dynamic Anatomic Model. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566465_42
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DOI: https://doi.org/10.1007/11566465_42
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