Label-efficient Deep Learning for Medical Image Analysis

Speaker: Dr. Hao CHEN
         Assistant Professor
         Department of Computer Science and Engineering

Title:  "Label-efficient Deep Learning for Medical Image Analysis"

Date:   Monday, 15 November 2021

Time:   4:00pm - 5:00pm

Venue:  Lecture Theater F (Leung Yat Sing Lecture Theater)
        (near lift 25/26, HKUST)

Zoom link:

Meeting ID:     955 3204 9042
Passcode:       CSE

**Note to CSE PGs with NIHK status, please attend the seminar via zoom**


Artificial intelligence, especially deep learning with large-scale
annotated datasets, has dramatically advanced the recognition performance
in many domains including speech recognition, visual recognition and
natural language processing. Despite its breakthroughs in above domains,
its application to medical image analysis remains yet to be further
explored, where large-scale fully and high-quality annotated datasets are
not easily accessible. In this talk, I will share our recent progress on
developing label-efficient learning methods by leveraging an abundance of
weakly-labeled and/or unlabeled datasets for medical image analysis, with
application to disease diagnosis, lesion localization and segmentation.


Dr. Hao CHEN is an Assistant Professor at the Department of Computer
Science and Engineering, Hong Kong University of Science and Technology.
His research mainly focuses on medical image analysis and deep learning.
He received the Ph.D. degree from The Chinese University of Hong Kong
(CUHK) in 2017. He was a postdoctoral research fellow in CUHK and a
visiting scholar in Utrecht University Medical Center previously. He also
has rich industrial research experience including Siemens and co-founded a
startup. He has 50+ publications and holds a dozen of patents in AI and
medical image analysis. He received several premium awards including Best
Paper Award in MIAR 2016, MICCAI Young Scientist Publication Impact Award
in 2019. He serves as the program committee of multiple international
conferences including Area Chair of MICCAI 2021, ISBI 2022 and SPC of AAAI
2022, etc. He also led the team winning 15+ medical grand challenges.