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densesharp's Introduction

Bio.

I am a final-year PhD at Shanghai Jiao Tong University, advised by Prof. Bingbing Ni. I received BEng and MEng degrees from the same university, and a double master's degree in France. I was a visiting research fellow in the Visual Computing Group at Harvard University. I am now visiting EPFL, Switzerland, working with Prof. Pascal Fua. I have authored 30+ papers on prestigious journals/conferences, e.g., Cancer Research, eBioMedicine, CVPR, MICCAI, NeurIPS, ICCV, and ICLR. I have been a reviewer for 10+ top-tier venues, a top-ranking participant for several AI competitions, and the lead organizer for MICCAI 2020 RibFrac Challenge. My research interests center around the interdisciplinary field of medical image analysis and 3D computer vision. Currently, I have been primarily investigating geometric deep learning in biomedical applications.

Research Projects

Preprint / Technical Reports

Publications

  • MedMNIST/MedMNIST: 18 MNIST-like Datasets for 2D and 3D Biomedical Image Classification: pip install medmnist #stars:577 #forks:96
  • M3DV/RibSeg: [MICCAI'21] RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans #stars:19 #forks:5
  • M3DV/ACSConv: [IEEE JBHI] Reinventing 2D Convolutions for 3D Images #stars:83 #forks:13
  • M3DV/FracNet: [EBioMedicine] Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet #stars:39 #forks:17
  • TrustworthyDL/LeBA: [NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback #stars:21 #forks:4
  • M3DV/SimTA: [MICCAI'20] MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response #stars:6 #forks:0
  • M3DV/AlignShift: [MICCAI'21] A3D + [MICCAI'20] AlignShift: A Codebase for Universal Lesion Detection (DeepLesion) #stars:36 #forks:8
  • duducheng/DenseSharp: [Cancer Research] 3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas #stars:109 #forks:56

Educational Projects

  • M3DV/Kickstart: Study route for learners in machine learning / deep learning / computer vision #stars:67 #forks:16
  • duducheng/2048-api: Educational API for developing ML (imitation learning or reinforcement learning) agents to play game 2048 #stars:115 #forks:113
  • duducheng/clustering_tutorial: A Tutorial of KMeans(++), GMM and Spectral Clustering #stars:23 #forks:10

Misc.

Total Stars: 1254. Total Forks: 379. Updated on May 02, 2022.

densesharp's People

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densesharp's Issues

Question about the evaluation metrics.

Hi~

I am a student of Beijing Institute of Technology. And we have some samples from hospital. I am very excited about your job on pathological subset classification.

I want to reproduce this work with pytorch, but the result is not good. I want to confirm where is the problem arise, data quality or bug code(pytorch).

When I run the code of yours, I found your metrics, f-measure, precision and recall are all calculated on binary classification. There is not multi-class metric in your code. Is there some wrong in my understanding? Thank you very much!!

Eric Kani

3Dslicer 画ROI

您好!!有一个小白问题请教下您,就是我用3Dslicer画出的ROI最后导出为nii文件,ROI数据矩阵大小和CT图的不一致,想问下你们是怎么处理的呢??谢谢啦

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