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
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