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ABOUT ME
ABOUT ME
Currently, I am a CS Ph.D. student at Johns Hopkins University, under the advisement of Prof. Alan Yuille.
I received my MSE and BSE degrees from Johns Hopkins University and Wuhan University in 2024 and 2022, respectively. I've worked as a research intern at Philips Research (2024), Johns Hopkins University (2023), Microsoft Research Asia (2022), Tencent Wesure (2021), and Kwaishou (2020).
My research interests are now focused on multimodal large language models (MLLM) and generative models (GenAI). Previously, I concentrated on scalable model training, dataset curation, and annotation for medical imaging.
Email address: johnson111788[at]gmail[dot]com
Other links: Google Scholar, LinkedIn, CV
NEWS
(2024/9) Our paper is accepted to NeurIPS'24.
(2024/6) Our paper is accepted to MICCAI'24.
(2023/10) Our paper is accepted to MIR'24.
(2023/6) Our paper is accepted to MICCAI'23.
(2023/1) Started my Ph.D. journey at Johns Hopkins University.
(2022/8) Our paper DGNet is accepted to MIR'23.
(2022/8) Our paper PNS+ is accepted to MIR'22.
(2022/6) I received the First Prize for Outstanding Academic College Students - China Computer Federation (CCF).
(2021/3) Our paper PNS-Net is accepted to MICCAI'21 with Student Travel Award (5.8%).
SELECTED PUBLICATIONS
* : Equal contribution, † : Corresponding Author
Preprint
Preprint
Conference Publications
Conference Publications
2024
2024
Embracing Massive Medical Data
Yu-Cheng Chou, Zongwei Zhou†, Alan Yuille
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
[PDF] [Code] [Official version]
2023
2023
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Bowen Li, Yu-Cheng Chou, Shuwen Sun, Hualin Qiao, Alan Yuille, Zongwei Zhou†
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023
[PDF] [Code] [Official version]
Scaling Temporal and Volumetric Datasets for Tumor Localization Without Per-Pixel Annotations
Yu-Cheng Chou, Bowen Li, Alan Yuille, Zongwei Zhou†
Radiological Society of North America (RSNA), 2023
[PDF] [Code] [Official version]
2022
2022
Determining Effective and Efficient Annotation Strategies to Curate Large-scale Colonoscopy Video Datasets for Polyp Detection
Yu-Cheng Chou, Deng-Ping Fan, Alan Yuille†, Zongwei Zhou
Radiological Society of North America (RSNA), 2022
[Oral, Accept rate = 930/10,400 = 9%]
[PDF] [Code] [Official version]
2021
2021
Progressively Normalized Self-Attention Network for Video Polyp Segmentation
Ge-Peng Ji*, Yu-Cheng Chou*, Deng-Ping Fan†, Geng Chen, Huazhu Fu, Debesh Jha, and Ling Shao
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
[Early Accept, Accept rate = 13% | Student Travel Award, Rate = 95/1630 = 5.8%]
[PDF] [Code] [Official version]
Journal Publications
Journal Publications
2024
2024
Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data
Yu-Cheng Chou, Bowen Li, Deng-Ping Fan, Alan Yuille, Zongwei Zhou†
Machine Intelligence Research (MIR), 2024, 1-13.
[PDF] [Code] [Official version]
2023
2023
Deep Gradient Learning for Efficient Camouflaged Object Detection
Ge-Peng Ji, Deng-Ping Fan†, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, Luc Van Gool.
Machine Intelligence Research (MIR), 2023, 20 (1): 92-108.
[PDF] [Code] [Official version]
2022
2022
Video Polyp Segmentation: A Deep Learning Perspective
Ge-Peng Ji*, Guobao Xiao*, Yu-Cheng Chou*, Deng-Ping Fan†, Kai Zhao, Geng Chen, Huazhu Fu, Luc Van Gool.
Machine Intelligence Research (MIR), 2022, 19 (6): 531-549.
[PDF] [Code] [Official version]
2021
2021
Automatic Polyp and Instrument Segmentation in MedAI-2021
Yu-Cheng Chou
Nordic Machine Intelligence (NMI), 2021, 1 (1): 17-19.
[MedAI-2021 Challenge Rank 2nd]
[PDF] [Code]
SERVICES
Reviewer for the conference
Challenge Chair: Body Maps: Towards 3D Atlas of Human Body (MICCAI 2024, ISBI 2024).
Reviewer for the conference
NeurIPS 2024, ICML 2024, AISTATS 2025, MICCAI 2024/2023, IEEE ICIP 2022, and IJECES 2022/2021
Reviewer for the journal
Transactions on Image Processing, Machine Intelligence Research, Computer Methods and Programs in Biomedicine, Sensors, Scientific Reports, Bioengineering, The Visual Computer, and Diagnostics.
PROJECTS
GALLERY
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