A 3-D Active Shape Model Driven by Fuzzy Inference: Application to Cardiac CT and MR

Abstract--Manual quantitative analysis of cardiac left ventricular function using Multislice CT and MR is arduous because of the large data volume. In this paper, we present a 3-D active shape model (ASM) for semiautomatic segmentation of cardiac CT and MR volumes, without the requirement of retraining the underlying statistical shape model. A fuzzy c-means based fuzzy inference system was incorporated into the model. Thus, relative gray-level differences instead of absolute gray values were used for classification of 3-D regions of interest (ROIs), removing the necessity of training different models for different modalities/acquisition protocols. The 3-D ASM was evaluated using 25 CT and 15 MR datasets. Automatically generated contours were compared to expert contours in 100 locations. For CT, 82.4% of epicardial contours and 74.1% of endocardial contours had a maximum error of 5 mm along 95% of the contour arc length. For MR, those numbers were 93.2%

• Type: Journal
• Year: 2008
• Where: TITB
• Authors: Hans C. van Assen, Mikhail G. Danilouchkine, M. S. Dirksen, Johan H. C. Reiber, Boudewijn P. F. Lelieveldt
• Keywords: 3-D Active Shape, Shape Model, Statistical Shape Model, TITB 2008