151 citations · 325 across the 19 of their papers we have counts for
7 papers · 1 filter
The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
Jun Ma, Ronald Xie, Shamini Ayyadhury +37
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…
mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation
Yao Zhang, Nanjun He, Jiawei Yang +6
Accurate brain tumor segmentation from Magnetic Resonance Imaging (MRI) is desirable to joint learning of multimodal images. However, in clinical practice, it is not always possibl…
Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
Yao Zhang, Jiawei Yang, Jiang Tian +4
Liver cancer is one of the most common cancers worldwide. Due to inconspicuous texture changes of liver tumor, contrast-enhanced computed tomography (CT) imaging is effective for t…
Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer
Yao Zhang, Jiawei Yang, Feng Hou +6
Accurate segmentation of cardiac structures can assist doctors to diagnose diseases, and to improve treatment planning, which is highly demanded in the clinical practice. However,…
Modality-Pairing Learning for Brain Tumor Segmentation
Yixin Wang, Yao Zhang, Feng Hou +5
Automatic brain tumor segmentation from multi-modality Magnetic Resonance Images (MRI) using deep learning methods plays an important role in assisting the diagnosis and treatment…
Semantic Feature Attention Network for Liver Tumor Segmentation in Large-scale CT database
Yao Zhang, Cheng Zhong, Yang Zhang +2
Liver tumor segmentation plays an important role in hepatocellular carcinoma diagnosis and surgical planning. In this paper, we propose a novel Semantic Feature Attention Network (…
Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes
Yao Zhang, Yixin Wang, Feng Hou +4
Automated segmentation of kidney and tumor from 3D CT scans is necessary for the diagnosis, monitoring, and treatment planning of the disease. In this paper, we describe a two-stag…