139 citations · 701 across the 36 of their papers we have counts for
38 papers
Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image Segmentation
Qingjie Zeng, Yutong Xie, Zilin Lu +2
Semi-supervised learning (SSL) has been proven beneficial for mitigating the issue of limited labeled data especially on the task of volumetric medical image segmentation. Unlike p…
Tackling the Incomplete Annotation Issue in Universal Lesion Detection Task By Exploratory Training
Xiaoyu Bai, Benteng Ma, Changyang Li +1
Universal lesion detection has great value for clinical practice as it aims to detect various types of lesions in multiple organs on medical images. Deep learning methods have show…
TEC-Net: Vision Transformer Embrace Convolutional Neural Networks for Medical Image Segmentation
Rui Sun, Tao Lei, Weichuan Zhang +3
The hybrid architecture of convolution neural networks (CNN) and Transformer has been the most popular method for medical image segmentation. However, the existing networks based o…
An End-to-End Framework For Universal Lesion Detection With Missing Annotations
Xiaoyu Bai, Yong Xia
Fully annotated large-scale medical image datasets are highly valuable. However, because labeling medical images is tedious and requires specialized knowledge, the large-scale data…
ProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image Segmentation
Shishuai Hu, Zehui Liao, Yong Xia
The domain discrepancy existed between medical images acquired in different situations renders a major hurdle in deploying pre-trained medical image segmentation models for clinica…
Learning from partially labeled data for multi-organ and tumor segmentation
Yutong Xie, Jianpeng Zhang, Yong Xia +1
Medical image benchmarks for the segmentation of organs and tumors suffer from the partially labeling issue due to its intensive cost of labor and expertise. Current mainstream app…
Boundary-Aware Network for Abdominal Multi-Organ Segmentation
Shishuai Hu, Zehui Liao, Yong Xia
Automated abdominal multi-organ segmentation is a crucial yet challenging task in the computer-aided diagnosis of abdominal organ-related diseases. Although numerous deep learning…
Boundary-Aware Network for Kidney Parsing
Shishuai Hu, Yiwen Ye, Zehui Liao +1
Kidney structures segmentation is a crucial yet challenging task in the computer-aided diagnosis of surgery-based renal cancer. Although numerous deep learning models have achieved…
Label Propagation for 3D Carotid Vessel Wall Segmentation and Atherosclerosis Diagnosis
Shishuai Hu, Zehui Liao, Yong Xia
Carotid vessel wall segmentation is a crucial yet challenging task in the computer-aided diagnosis of atherosclerosis. Although numerous deep learning models have achieved remarkab…
ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers
Yutong Xie, Jianpeng Zhang, Yong Xia +2
Although Transformers have successfully transitioned from their language modelling origins to image-based applications, their quadratic computational complexity remains a challenge…
HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging
Haozhe Jia, Chao Bai, Weidong Cai +2
In our previous work, , HNF-Net, high-resolution feature representation and light-weight non-local self-attention mechanism are exploited for brain tumor segmentation using m…
UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier
Yutong Xie, Jianpeng Zhang, Yong Xia +1
Self-supervised learning (SSL) opens up huge opportunities for medical image analysis that is well known for its lack of annotations. However, aggregating massive (unlabeled) 3D me…
Dual-Flow Transformation Network for Deformable Image Registration with Region Consistency Constraint
Xinke Ma, Yibo Yang, Yong Xia +1
Deformable image registration is able to achieve fast and accurate alignment between a pair of images and thus plays an important role in many medical image studies. The current de…
FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis
Yu Feng, Benteng Ma, Jing Zhang +3
In recent years, the security of AI systems has drawn increasing research attention, especially in the medical imaging realm. To develop a secure medical image analysis (MIA) syste…
Modeling Annotator Preference and Stochastic Annotation Error for Medical Image Segmentation
Zehui Liao, Shishuai Hu, Yutong Xie +1
Manual annotation of medical images is highly subjective, leading to inevitable and huge annotation biases. Deep learning models may surpass human performance on a variety of tasks…
Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image Segmentation
Shishuai Hu, Zehui Liao, Jianpeng Zhang +1
The domain gap caused mainly by variable medical image quality renders a major obstacle on the path between training a segmentation model in the lab and applying the trained model…
PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images
Haozhe Jia, Haoteng Tang, Guixiang Ma +4
Automated and accurate segmentation of the infected regions in computed tomography (CT) images is critical for the prediction of the pathological stage and treatment response of CO…
Boundary-aware Graph Reasoning for Semantic Segmentation
Haoteng Tang, Haozhe Jia, Weidong Cai +3
In this paper, we propose a Boundary-aware Graph Reasoning (BGR) module to learn long-range contextual features for semantic segmentation. Rather than directly construct the graph…
Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction
Zehui Liao, Yutong Xie, Shishuai Hu +1
Lung nodule malignancy prediction is an essential step in the early diagnosis of lung cancer. Besides the difficulties commonly discussed, the challenges of this task also come fro…
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
Yutong Xie, Jianpeng Zhang, Chunhua Shen +1
Convolutional neural networks (CNNs) have been the de facto standard for nowadays 3D medical image segmentation. The convolutional operations used in these networks, however, inevi…
H2NF-Net for Brain Tumor Segmentation using Multimodal MR Imaging: 2nd Place Solution to BraTS Challenge 2020 Segmentation Task
Haozhe Jia, Weidong Cai, Heng Huang +1
In this paper, we propose a Hybrid High-resolution and Non-local Feature Network (H2NF-Net) to segment brain tumor in multimodal MR images. Our H2NF-Net uses the single and cascade…
Inter-layer Transition in Neural Architecture Search
Benteng Ma, Jing Zhang, Yong Xia +1
Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and arc…
Inter-slice Context Residual Learning for 3D Medical Image Segmentation
Jianpeng Zhang, Yutong Xie, Yan Wang +1
Automated and accurate 3D medical image segmentation plays an essential role in assisting medical professionals to evaluate disease progresses and make fast therapeutic schedules.…
PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation
Yutong Xie, Jianpeng Zhang, Zehui Liao +2
It has been widely recognized that the success of deep learning in image segmentation relies overwhelmingly on a myriad amount of densely annotated training data, which, however, a…