S
Shanlin Sun
Researcher at University of California, Irvine
Publications - 19
Citations - 156
Shanlin Sun is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 3, co-authored 8 publications receiving 22 citations.
Papers
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Proceedings ArticleDOI
Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow
TL;DR: A new model called Neural Diffeomorphic Flow (NDF) is proposed to learn deep implicit shape templates, representing shapes as conditional diffeomorphic deformations of templates, intrinsically preserving shape topologies.
Proceedings ArticleDOI
Attentionanatomy: A Unified Framework for Whole-Body Organs at Risk Segmentation Using Multiple Partially Annotated Datasets
TL;DR: This paper's proposed end-to-end convolutional neural network model, called AttentionAnatomy, can be jointly trained with three partially annotated datasets, segmenting OARs from whole body, and presented significant improvements in both Sørensen-Dice coefficient (DSC) and 95% Hausdorff distance compared to the baseline model.
Proceedings ArticleDOI
Diffeomorphic Image Registration with Neural Velocity Field
TL;DR: A new optimization-based method named DNVF (Diffeomorphic Image Registration with Neural Velocity Field) which utilizes deep neural network to model the space of admissible transformations, and a cascaded image registration framework (Cas-DNVF) by combining the benefits of both optimization and learning based methods.
Journal ArticleDOI
MIRNF: Medical Image Registration via Neural Fields
TL;DR: A new deep-neural net based image registration framework, named MIRNF, which represents the correspondence mapping with a continuous function implemented via Neural Fields, and proposes a hybrid coordinate sampler along with a cascaded architecture to achieve the high-similarity mapping performance and low-distortion deformation performance.
Proceedings ArticleDOI
Identity-Aware Hand Mesh Estimation and Personalization from RGB Images
Deying Kong,Linguang Zhang,Liangjian Chen,Haoyu Ma,Xiangyi Yan,Shanlin Sun,Xingwei Liu,Kun-Hee Han,Xiaohui Xie +8 more
TL;DR: This paper proposes an identity-aware hand mesh estimation model, which can incorporate the identity information represented by the intrinsic shape parameters of the subject, and proposes a novel personalization pipeline to calibrate the intrinsicshape parameters using only a few unlabeled RGB images of thesubject.