most citedKeypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2024

CUNSB-RFIE: Context-aware Unpaired Neural Schrödinger Bridge in Retinal Fundus Image Enhancement

Xuanzhao Dong, Vamsi Krishna Vasa, Wenhui Zhu +7

Retinal fundus photography is significant in diagnosing and monitoring retinal diseases. However, systemic imperfections and operator/patient-related factors can hinder the acquisi…

cs.CV2024

AMG: Avatar Motion Guided Video Generation

Zhangsihao Yang, Mengyi Shan, Mohammad Farazi +4

Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in natu…

cs.CV20231 cited

Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation

Zhangsihao Yang, Mengwei Ren, Kaize Ding +2

Pretraining CNN models (i.e., UNet) through self-supervision has become a powerful approach to facilitate medical image segmentation under low annotation regimes. Recent contrastiv…

cs.CV2023

TetCNN: Convolutional Neural Networks on Tetrahedral Meshes

Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu +2

Convolutional neural networks (CNN) have been broadly studied on images, videos, graphs, and triangular meshes. However, it has seldom been studied on tetrahedral meshes. Given the…

eess.IV2023

OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing

Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu +5

Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operator…