activity
20182022
most citedCross-view Relation Networks for Mammogram Mass Detection

16 citations · 19 across the 4 of their papers we have counts for

collaborators

8 papers

eess.IV20221 cited

Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training

Shu Zhang, Zihao Li, Hong-Yu Zhou +2

The difficulties in both data acquisition and annotation substantially restrict the sample sizes of training datasets for 3D medical imaging applications. As a result, constructing…

cs.CV2020

Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices

Shu Zhang, Jincheng Xu, Yu-Chun Chen +4

Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D conte…

cs.CV2019

Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks

Xiang Li, Jiechao Ma, Hongwei Li

Early diagnosis of pathological invasiveness of pulmonary adenocarcinomas using computed tomography (CT) imaging would alter the course of treatment of adenocarcinomas and subseque…

eess.IV2019

Automatic Calcium Scoring in Cardiac and Chest CT Using DenseRAUnet

Jiechao Ma, Rongguo Zhang

Cardiovascular disease (CVD) is a common and strong threat to human beings, featuring high prevalence, disability and mortality. The amount of coronary artery calcification (CAC) i…

cs.CV20192 cited

Delving Deep into Liver Focal Lesion Detection: A Preliminary Study

Jiechao Ma, Yingqian Chen, Yu Chen +4

Hepatocellular carcinoma (HCC) is the second most frequent cause of malignancy-related death and is one of the diseases with the highest incidence in the world. Because the liver i…

cs.CV201916 cited

Cross-view Relation Networks for Mammogram Mass Detection

Jiechao Ma, Sen Liang, Xiang Li +4

Mammogram is the most effective imaging modality for the mass lesion detection of breast cancer at the early stage. The information from the two paired views (i.e., medio-lateral o…