16 citations · 42 across the 9 of their papers we have counts for
7 papers · 1 filter
Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation
Shengbo Gao, Ziji Zhang, Jiechao Ma +2
Semi-supervised learning has become increasingly popular in medical image segmentation due to its ability to leverage large amounts of unlabeled data to extract additional informat…
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…
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…
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…
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…
Towards Photo-Realistic Visible Watermark Removal with Conditional Generative Adversarial Networks
Xiang Li, Chan Lu, Danni Cheng +5
Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential. To evaluate and improve the…
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images
Jiechao Ma, Xiang Li, Hongwei Li +4
Early diagnosis of pulmonary nodules (PNs) can improve the survival rate of patients and yet is a challenging task for radiologists due to the image noise and artifacts in computed…