69 citations · 207 across the 11 of their papers we have counts for
8 papers · 1 filter
Mixed Transformer U-Net For Medical Image Segmentation
Hongyi Wang, Shiao Xie, Lanfen Lin +4
Though U-Net has achieved tremendous success in medical image segmentation tasks, it lacks the ability to explicitly model long-range dependencies. Therefore, Vision Transformers h…
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
Yue Zhang, Chengtao Peng, Liying Peng +8
Multi-phase computed tomography (CT) images provide crucial complementary information for accurate liver tumor segmentation (LiTS). State-of-the-art multi-phase LiTS methods usuall…
Graph-based Pyramid Global Context Reasoning with a Saliency-aware Projection for COVID-19 Lung Infections Segmentation
Huimin Huang, Ming Cai, Lanfen Lin +9
Coronavirus Disease 2019 (COVID-19) has rapidly spread in 2020, emerging a mass of studies for lung infection segmentation from CT images. Though many methods have been proposed fo…
PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Images
Yingying Xu, Ming Cai, Lanfen Lin +10
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is new…
VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data
Yinhao Li, Yutaro Iwamoto, Lanfen Lin +2
Deep learning-based super-resolution (SR) techniques have generally achieved excellent performance in the computer vision field. Recently, it has been proven that three-dimensional…
Unsupervised MRI Super-Resolution Using Deep External Learning and Guided Residual Dense Network with Multimodal Image Priors
Yutaro Iwamoto, Kyohei Takeda, Yinhao Li +2
Deep learning techniques have led to state-of-the-art image super resolution with natural images. Normally, pairs of high-resolution and low-resolution images are used to train the…
Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network
Rui Xu, Tiantian Liu, Xinchen Ye +1
Many deep learning based methods have been proposed for retinal vessel segmentation, however few of them focus on the connectivity of segmented vessels, which is quite important fo…
UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation
Huimin Huang, Lanfen Lin, Ruofeng Tong +6
Recently, a growing interest has been seen in deep learning-based semantic segmentation. UNet, which is one of deep learning networks with an encoder-decoder architecture, is widel…