Aug 29, 2022 · At the core of our approach lies a deep convolutional framework that approximates spectral bases and optimizes volumetric descriptors. The multi ...
This paper presents a data-driven spectral mapping-based correspondence framework to handle the intrinsic correspondence of anatomical structures.
This paper presents a data-driven spectral mapping-based correspondence framework to handle the intrinsic correspondence of anatomical structures. At the core ...
Aug 29, 2022 · We showcase the efficacy of the core modules, i.e., the spectral embedding approximation and descriptor learning, for volumetric image ...
This paper presents a novel and efficient correspondence framework via low-dimensional spectral mapping to handle the intrinsic correspondence of anatomical ...
Sep 27, 2021 · This paper presents a novel and efficient correspondence framework via low-dimensional spectral mapping to handle the intrinsic correspondence of anatomical ...
This paper presents a novel and efficient correspondence framework via low-dimensional spectral mapping to handle the intrinsic correspondence of anatomical ...
Dense correspondence of deformable volumetric images via deep spectral embedding and descriptor learning. Medical Image Anal. 82: 102604 (2022). [j4]. view.
Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence ... Deep learning in medical image registration: a ...
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Dense correspondence of deformable volumetric images via deep spectral embedding and descriptor learning. · Automatic construction of correspondences for tubular ...