139 citations · 247 across the 7 of their papers we have counts for
9 papers
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…
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…
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…
DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets
Jianpeng Zhang, Yutong Xie, Yong Xia +1
Due to the intensive cost of labor and expertise in annotating 3D medical images at a voxel level, most benchmark datasets are equipped with the annotations of only one type of org…