25 citations · 82 across the 21 of their papers we have counts for
8 papers · 1 filter
HQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance
Chunming He, Kai Li, Guoxia Xu +5
Unpaired Medical Image Enhancement (UMIE) aims to transform a low-quality (LQ) medical image into a high-quality (HQ) one without relying on paired images for training. While most…
Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification
ChengHui Yu, MingKang Tang, ShengGe Yang +7
Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the signific…
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction
Jiangpeng Yan, Chenghui Yu, Hanbo Chen +4
Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.…
Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning
Jiawei Yang, Hanbo Chen, Jiangpeng Yan +2
Few-shot learning is an established topic in natural images for years, but few work is attended to histology images, which is of high clinical value since well-labeled datasets and…
All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation
Zhe Xu, Yixin Wang, Donghuan Lu +6
Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially,…
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +2
Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most dee…
Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +4
Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we propose a…
Neural Architecture Search for Compressed Sensing Magnetic Resonance Image Reconstruction
Jiangpeng Yan, Shuo Chen, Yongbing Zhang +1
Recent works have demonstrated that deep learning (DL) based compressed sensing (CS) implementation can accelerate Magnetic Resonance (MR) Imaging by reconstructing MR images from…