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20192023
most citedAFTer-UNet: Axial Fusion Transformer UNet for Medical Image Segmentation

11 citations · 25 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CV20231 cited

Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction

Shanlin Sun, Thanh-Tung Le, Chenyu You +6

We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction. Specifically, Hybrid-CSR begin…

cs.CV20222 cited

PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation

Haoyu Ma, Zhe Wang, Yifei Chen +6

Recently, the vision transformer and its variants have played an increasingly important role in both monocular and multi-view human pose estimation. Considering image patches as to…

cs.CV20222 cited

Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow

Shanlin Sun, Kun Han, Deying Kong +3

Deep Implicit Functions (DIFs) represent 3D geometry with continuous signed distance functions learned through deep neural nets. Recently DIFs-based methods have been proposed to h…

cs.CV20212 cited

Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

Hao Tang, Xingwei Liu, Shanlin Sun +2

Although having achieved great success in medical image segmentation, deep convolutional neural networks usually require a large dataset with manual annotations for training and ar…

cs.CV2019

NoduleNet: Decoupled False Positive Reductionfor Pulmonary Nodule Detection and Segmentation

Hao Tang, Chupeng Zhang, Xiaohui Xie

Pulmonary nodule detection, false positive reduction and segmentation represent three of the most common tasks in the computeraided analysis of chest CT images. Methods have been p…

cs.CV20193 cited

Automatic Pulmonary Lobe Segmentation Using Deep Learning

Hao Tang, Chupeng Zhang, Xiaohui Xie

Pulmonary lobe segmentation is an important task for pulmonary disease related Computer Aided Diagnosis systems (CADs). Classical methods for lobe segmentation rely on successful d…