DocumentCode :
2701042
Title :
A model based contour searching method
Author :
Tang, Yingjie ; He, Lei ; Wang, Xun ; Wee, William G.
Author_Institution :
Dept. of Electr. & Comput. Eng. & Comput. Sci., Cincinnati Univ., OH, USA
fYear :
2000
fDate :
2000
Firstpage :
347
Lastpage :
354
Abstract :
A two-step model based approach to a contour extraction problem is developed to provide a solution to more challenging contour extraction problems of biomedical images. A biomedical contour image is initially processed by a deformable contour method to obtain a first order approximation of the contour. The two-step model includes a linked contour model and a posteriori probability model. Initially, the output contour from the deformable contour method is matched against the linked contour model for both model detection and corresponding landmark contour points identification. Segments obtained from these landmarks are matched for errors. Larger error are then passed on to a regionalized a posteriori probability model for further fine tuning to obtain a final result. Experiments on both MR brain images are most encouraging
Keywords :
biomedical MRI; brain; edge detection; medical image processing; modelling; MR brain images; MRI; a posteriori probability model; biomedical contour image; deformable contour method; first order approximation; medical diagnostic imaging; model based contour searching method; regionalized a posteriori probability model; Biomedical computing; Biomedical imaging; Brain; Deformable models; Fourier transforms; Image segmentation; Shape; Spline; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Informatics and Biomedical Engineering, 2000. Proceedings. IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7695-0862-6
Type :
conf
DOI :
10.1109/BIBE.2000.889627
Filename :
889627
Link To Document :
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