activity
20192024
most citedA Survey of Visual Transformers

42 citations · 121 across the 17 of their papers we have counts for

collaborators
Showing eess.IVShow all

7 papers · 1 filter

eess.IV2022★ 12 cited

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…

eess.IV2022

Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models

Ashkan Khakzar, Yawei Li, Yang Zhang +5

One challenging property lurking in medical datasets is the imbalanced data distribution, where the frequency of the samples between the different classes is not balanced. Training…

eess.IV2021★ 10 cited

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…

eess.IV2021★ 8 cited

ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities

Yixin Wang, Yang Zhang, Yang Liu +6

Accurate segmentation of brain tumors from magnetic resonance imaging (MRI) is clinically relevant in diagnoses, prognoses and surgery treatment, which requires multiple modalities…

eess.IV2020★ 1 cited

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,…

eess.IV2020★ 15 cited

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…

eess.IV2019★ 1 cited

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 (…