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Zongwei Zhou
 

Email: zzhou82@jh.edu

Tel: 1-(480)738-2575

URL: www.zongweiz.com

Office: 248 Malone Hall, Johns Hopkins University, Baltimore, MD

Overview: Zongwei Zhou is a postdoctoral researcher at Johns Hopkins University advised by Bloomberg Distinguished Professor Alan Yuille. He received his Ph.D. in Biomedical Informatics at Arizona State University advised by Dr. Jianming Liang. He has also spent time at Mayo Clinic, University of California, Berkeley, and Université de Montréal. His research focuses on developing novel methodologies to minimize the annotation efforts for computer-aided diagnosis and medical imaging. In addition to two U.S. patents, Zongwei has published over ten peer-reviewed journal/conference articles, two of which received the MICCAI Young Scientist Award and Elsevier-MedIA Best Paper Award. Two of his journal publications have been ranked among the most popular articles in IEEE TMI and the highest-cited article in EJNMMI Research, respectively. Zongwei has been elected to the Guest Editor of Sensors; Reviewer of IEEE TPAMI, MedIA, Information Fusion, IEEE TMI; and he was on the Program Committee for MICCAI in 2020-21; AAAI in 2020-22; CVPR in 2022; ICCV in 2021, MIDL in 2022. ORCiD: 0000-0002-3154-9851

Education

Ph.D. Aug 2017-May 2021

Arizona State University

Department: Biomedical Informatics

Thesis: Towards Annotation-Efficient Deep Learning for Computer-Aided Diagnosis

Advisors: Dr. Jianming Liang

> View Dissertation    > View LaTeX    > View Talk    > View Slides    > View Transcript

B.S. Sep 2012-Jul 2016

Dalian University of Technology

Department: Computer Science

Thesis: Medical image classification based on deep learning
Advisor: Dr. Hongkai Wang

> View Dissertation    > View Slides

Experience

Postdoctoral Researcher June 2021-present

Johns Hopkins University

Group: Computational Cognition, Vision, and Learning (CCVL)

Projects: Detect signs of pancreatic cancer in CT scans earlier and with more accuracy than humans

Research Internship Jan 2018-July 2018

Centre Hospitalier de l’Université de Montréal

Group: Laboratoire clinique de traitement de l’image (LCTI)

Projects: Predictive model of colorectal cancer liver metastases response to chemotherapy

Joint collaboration: Imagia and MILA

Research Internship June 2017-Jul 2017

Mayo Clinic, Rochester MN

Group: Radiology Informatics Lab

Projects: Thyroid Ultrasound Imaging, Tumor Radiogenomics

Awards and Honors

 

Journal Publications

Medical Image Analysis

Models Genesis

Zongwei Zhou, Vatsal Sodha, Jiaxuan Pang, Michael B. Gotway, Jianming Liang*

MedIA Best Paper Award

> View Publication   > View Code   > View Slides

Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts

Zongwei Zhou, Jae Shin, Suryakanth Gurudu, Michael B. Gotway, Jianming Liang*

> View Publication   > View Code   > View Slides

Transactions on Medical Imaging

Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning

Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael Gotway, Jianming Liang*

> View Publication   > View Code

UNet++: Redesigning Skip Connections to Exploit Multi-Resolution Features in Image Segmentation

Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang*

> View Publication   > View Code

Journal of Digital Imaging

Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation

Zongwei Zhou, Jae Shin, Ruibin Feng, R. Todd Hurst, Christopher B. Kendall, Jianming Liang*

> View Publication

EJNMMI Research

Comparison of Machine Learning Methods for Classifying Mediastinal Lymph Node Metastasis of Non-small Cell Lung Cancer from 18F-FDG PET/CT Images

Hongkai Wang, Zongwei Zhou, Yingci Li, Zhonghua Chen, Peiou Lu, Wenzhi Wang, Wanyu Liu, Lijuan Yu*

> View Publication

Conference Publications

MLMI 2021

Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection

Nahid Ul Islam, Shiv Gehlot, Zongwei Zhou, Michael Gotway, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk
 

DART 2020

Parts2Whole: Self-supervised Contrastive Learning via Reconstruction

Ruibin Feng, Zongwei Zhou, Michael Gotway, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

MICCAI 2020

Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael Gotway, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

ICCV 2019

Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization

Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Yoshua Bengio, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

MICCAI 2019

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael Gotway, Jianming Liang*

Young Scientist Award

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

DLMIA 2018

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

CVPR 2017

Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally

Zongwei Zhou, Jae Shin, Lei Zhang, Suryakanth Gurudu, Michael Gotway, Jianming Liang*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

arXiv Preprints & Abstracts

arXiv Preprints

In-painting Radiography Images for Unsupervised Anomaly Detection

Tiange Xiang, Yongyi Lu, Alan L. Yuille, Chaoyi Zhang, Weidong Cai, Zongwei Zhou*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk
 

Learning from Temporal Gradient for Semi-supervised Action Recognition

Junfei Xiao, Longlong Jing, Lin Zhang, Ju He, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk
 

Data, Assemble: Leveraging Multiple Datasets with Heterogeneous and Partial Labels

Mintong Kang, Yongyi Lu, Alan Yuille, Zongwei Zhou*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk
 

Frequency of Rational Fractions on [0, 1] 

Zongwei Zhou, Dawei Lu*

> View Publication   > View Code   > View Slides   > View Poster   > View Talk

US Patents

Methods, Systems, and Media for Discriminating and Generating Translated Images

Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Jianming Liang

Granted on November 2, 2021; US Patent 11,164,021

Systems, Methods, and Apparatuses for Implementing a Multi-resolution Neural Network for Use with Imaging Intensive Applications Including Medical Imaging

Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang

Granted on November 2, 2021; US Patent 11,164,067

Invited Talks and Blogs

Invited Talks

Data, Assemble: Towards Efficient Medical Image Analysis 

MICCAI 2021 FLARE Challenge Keynote Oct 1, 2021

> View Blog    > View Slides    > View Talk
 

Towards Annotation-Efficient Deep Learning for Computer-Aided Diagnosis 

Medical Image Computing Seminar (MICS) Aug 3, 2021

> View Blog    > View Slides    > View Talk
 

The Will of Computer Vision

VALSE Student Webinar Jan 28, 2021

> View Blog    > View Slides    > View Talk

Computer-aided Diagnosis and Therapy in Medical Imaging

BMI Seminar Sep 4, 2020

> View Slides

Cost-Effective Computer-Aided Diagnosis of Lung Cancer in Chest Computed Tomography

Phoenix Symposium on Data Analytics in Healthcare Aug 13, 2020

> View Slides    > View Talk

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

AI Journal club Feb 29, 2020

> View Slides

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

Mila – Quebec Artificial Intelligence Institute Nov 11, 2019

> View Slides

3D Transfer Learning in Medical Image Analysis

AI Research Club Oct 24, 2019

> View Blog    > View Slides    > View Talk   

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

MICS Webinar Sep 24, 2019

> View Slides    > View Talk   

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

AI Research Club Sep 18, 2018

> View Blog    > View Slides    > View Talk

How to Cut Annotation Cost in Biomedical Imaging

Centre Hospitalier de l’Université de Montréal May 22, 2018

> View Slides

Hot Posts

研习U-Net

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Active Learning: 一个降低深度学习时间,空间,经济成本的解决方案

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简易的深度学习框架Keras代码解析与应用

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想申请美国博士的看过来!

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Zongwei Zhou

Postdoctoral Researcher
Department of Computer Science
Johns Hopkins University, Baltimore, MD