activity
20192023
most citedCross-Modality Deep Feature Learning for Brain Tumor Segmentation

290 citations · 373 across the 9 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

eess.IV2022★ 8 cited

UNet-2022: Exploring Dynamics in Non-isomorphic Architecture

Jiansen Guo, Hong-Yu Zhou, Liansheng Wang +1

Recent medical image segmentation models are mostly hybrid, which integrate self-attention and convolution layers into the non-isomorphic architecture. However, one potential drawb…

cs.CV2022

Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis

Gangming Zhao, Quanlong Feng, Chaoqi Chen +2

During clinical practice, radiologists often use attributes, e.g. morphological and appearance characteristics of a lesion, to aid disease diagnosis. Effectively modeling attribute…

cs.CV2022

Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance

Chengwei Pan, Gangming Zhao, Junjie Fang +6

Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to mu…

cs.CV2022

Domain Invariant Model with Graph Convolutional Network for Mammogram Classification

Churan Wang, Jing Li, Xinwei Sun +3

Due to its safety-critical property, the image-based diagnosis is desired to achieve robustness on out-of-distribution (OOD) samples. A natural way towards this goal is capturing o…

eess.IV2022

Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis

Yunlong Zhang, Xin Lin, Yihong Zhuang +6

Synthesizing a subject-specific pathology-free image from a pathological image is valuable for algorithm development and clinical practice. In recent years, several approaches base…

eess.IV2022★ 290 cited

Cross-Modality Deep Feature Learning for Brain Tumor Segmentation

Dingwen Zhang, Guohai Huang, Qiang Zhang +3

Recent advances in machine learning and prevalence of digital medical images have opened up an opportunity to address the challenging brain tumor segmentation (BTS) task by using d…