Spatial transformation and registration of brain images using elastically deformable models
Computer Vision and Image Understanding
An Adaptive-Focus Deformable Model Using Statistical and Geometric Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distribution of Prostrate Cancer for Optimized Biopsy Protocols
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
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This paper presents a methodology of creating a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and uses it for designing optimal needle biopsy strategies. In order to remove inter-individual morphological variability and determine the true variability in cancer position, an adaptive-focus deformable model (AFDM) is used to register and normalize prostate samples. Moreover, a probabilistic method is developed for designing optimal biopsy strategies that determine the locations and the number of needles by optimizing cancer detection probability. Vanous expenments demonstrate the performance of AFDM in registenng prostate samples for construction of the statistical atlas, and also validate the predictive power of our atlas-based optimal biopsy strategies in detecting prostate cancer.