282 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN9 papers
- Jinan UniversityCN9 papers
- National Astronomical ObservatoriesCN8 papers
- Peking UniversityCN7 papers
- The University of Texas Southwestern Medical CenterUS6 papers
- Kavli Institute for Theoretical SciencesCN5 papers
- Brera Astronomical ObservatoryIT3 papers
- Institute of Space SciencesES3 papers
- Nanjing University of Science and TechnologyCN3 papers
- Osservatorio Astronomico di PadovaIT3 papers
- South China University of TechnologyCN3 papers
- University of California San DiegoUS3 papers
11 papers · 1 filter
MDU-Net: Multi-scale Densely Connected U-Net for biomedical image segmentation
Jiawei Zhang, Yuzhen Jin, Jilan Xu +2
Biomedical image segmentation plays a central role in quantitative analysis, clinical diagnosis, and medical intervention. In the light of the fully convolutional networks (FCN) an…
A Multi-stage Framework with Context Information Fusion Structure for Skin Lesion Segmentation
Yujiao Tang, Feng Yang, Shaofeng Yuan +1
The computer-aided diagnosis (CAD) systems can highly improve the reliability and efficiency of melanoma recognition. As a crucial step of CAD, skin lesion segmentation has the uns…
Sequential Wnt Agonist then Antagonist Treatment Accelerates Tissue Repair and Minimizes Fibrosis
Xiao-Jun Tian, Dong Zhou, Haiyan Fu +5
Tissue fibrosis compromises organ function and occurs as a potential long-term outcome in response to acute tissue injuries. Currently, lack of mechanistic understanding prevents e…
Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features
Shulong Li, Panpan Xu, Bin Li +8
To predict lung nodule malignancy with a high sensitivity and specificity, we propose a fusion algorithm that combines handcrafted features (HF) into the features learned at the ou…
Sample size determination in superiority or non-inferiority clinical trials with time-to-event data under exponential, Weibull and Gompertz distributions
Dong Han, Yawen Hou, Zheng Chen
To examine the effect of exponential, Weibull and Gompertz distributions on sample size determination for superiority trials (STs) or non-inferiority trials (NTs) with time-to-even…
Radon Inversion via Deep Learning
Ji He, Jianhua Ma
Radon transform is widely used in physical and life sciences and one of its major applications is the X-ray computed tomography (X-ray CT), which is significant in modern health ex…
Denoising of 3-D Magnetic Resonance Images Using a Residual Encoder-Decoder Wasserstein Generative Adversarial Network
Maosong Ran, Jinrong Hu, Yang Chen +4
Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is a critical step in medical image analysis. Over the past few years, many algorithms with impressive p…
Statistical inference methods for cumulative incidence function curves at a fixed point in time
Jinbao Chen, Yawen Hou, Zheng Chen
Competing risks data arise frequently in clinical trials. When the proportional subdistribution hazard assumption is violated or two cumulative incidence function (CIF) curves cros…
Automatic multi-objective based feature selection for classification
Zhiguo Zhou, Shulong Li, Genggeng Qin +3
Objective: Accurately classifying the malignancy of lesions detected in a screening scan is critical for reducing false positives. Radiomics holds great potential to differentiate…
Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network
Shumao Pang, Stephanie Leung, Ilanit Ben Nachum +2
Automated quantitative measurement of the spine (i.e., multiple indices estimation of heights, widths, areas, and so on for the vertebral body and disc) is of the utmost importance…
Sample size for a non-inferiority clinical trial with time-to-event data in the presence of competing risks
Dong Han, Zheng Chen, Yawen Hou
The analysis and planning methods for competing risks model have been described in the literatures in recent decades, and non-inferiority clinical trials are helpful in current pha…