Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A new point matching algorithm for non-rigid registration
Computer Vision and Image Understanding - Special issue on nonrigid image registration
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Validation of computer-aided detection and intervention procedures for prostate cancer is still a challenging issue. Despite the increasing accuracy of prostate image analysis tools, in vivo and in silico validations are necessary before they can be deployed in clinical routine. In this study, we developed a statistical atlas of prostate morphology for construction of realistic digital and physical phantoms. We have been interested in modeling the gland's zonal anatomy as defined by the peripheral zone and the central gland. Magnetic Resonance Imaging studies from 30 patients were used. Mean shape and most relevant deformations for prostate structures were computed using principal component analysis. The resulting statistical atlas has been used in image simulation and the design of a physical phantom of the prostate.