Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching
Abstract
A non-rigid MR-TRUS image registration framework is proposed for prostate interventions. The registration framework consists of a convolutional neural networks (CNN) for MR prostate segmentation, a CNN for TRUS prostate segmentation and a point-cloud based network for rapid 3D point cloud matching. Volumetric prostate point clouds were generated from the segmented prostate masks using tetrahedron meshing. The point cloud matching network was...
Paper Details
Title
Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching
Published Date
Jan 1, 2021
Journal
Volume
67
Pages
101845 - 101845
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