Automatic segmentation of articulated structures
Disclosed herein is a framework for segmenting articulated structures. In accordance with one aspect, the framework receives a target image, a reference image, statistical shape models, local appearance models and a learned landmark detector. The framework may automatically detect first centerline landmarks along centerlines of articulated structures in the target image using the learned landmark detector. The framework may then determine a non-rigid transformation function that registers second centerline landmarks along centerlines of articulated structures in the reference image with the first centerline landmarks. Mean shapes of the statistical shape models may then be deformed to the target image space by applying the non-rigid transformation function on the mean shapes. The framework may further search for candidate points in the mean shapes using the local appearance models. The mean shapes may be fitted to the candidate points to generate a segmentation mask.
Siemens Medical Solutions USA, Inc.
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Xiang Sean Yiqiang Fitsum Aklilu Gerardo Yoshihisa Zhigang Shu
Zhou Zhan Reda Hermosillo Valadez Shinagawa Peng Liao