Events

AI-driven Automated Medical Image Analysis

Lecture / Panel
 
For NYU Community

Dr. YingLi Tian in blue cardigan smiling for the camera

Speaker

Dr. YingLi Tian
City College of New York (CCNY)

Title

"AI-driven Automated Medical Image Analysis"

Abstract

Medical imaging has been applied widely in many clinical diagnoses to detect and differentiate abnormalities. Manual analyzing medical images demands attention and is time-consuming, requiring well-trained expertise. The speed, fatigue, and experience may limit the diagnostic performance, leading to delays and even false diagnoses that significantly impact patient treatment. Therefore, developing AI-driven automated medical image analysis systems are crucial for timely clinical diagnosis. In this talk, I will share our research on two topics: 1) Contrast-enhanced medical images to highlight the internal structure of blood vessels and organs; 2) Cancer diagnosis with high sensitivity and specificity to detect, segment, and classify abnormality on medical images. The talk will be concluded with a discussion of potential future research trends.

About Speaker

Dr. YingLi Tian is a CUNY Distinguished Professor in Electrical Engineering Department at the City College of New York (CCNY) and Computer Science Department at Graduate Center of the City University of New York (CUNY). She is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), as well as a Fellow of International Association of Pattern Recognition (IAPR). She received her PhD from the Department of Electronic Engineering at the Chinese University of Hong Kong in 1996. Her research interests include computer vision, machine learning, artificial intelligence, assistive technology, medical imaging analysis, and remote sensing. She has published more than 240 peer-reviewed papers in journals and conferences in these areas with 24,000+ citations and holds 29 issued patents.

She is a pioneer in automatic facial expression analysis, human activity understanding, and assistive technology. Before joining CCNY in 2008, Dr. Tian was a research staff member at IBM T. J. Watson Research Center and led the video analytics team. She received the IBM Outstanding Innovation Achievement Award in 2007 and the IBM Invention Achievement Awards from 2002 to 2007. She serves as an associate editor for IEEE Trans. on Multimedia (TMM), Computer Vision and Image Understanding (CVIU), Journal of Visual Communication and Image Representation (JVCI), and Machine Vision and Applications (MVAP.)