Online Research Seminar
3:00 pm, Thursday, 23 June 2022

The seminar will be on topics from my ongoing research projects. The first two topics will be on biomedical image analysis projects that I pursue with collaborators. I will start with a novel methodology for MRI image registration. The first involves a statistical estimation of the registration as the non-parametric Bayesian posterior expectation. This estimate undergoes Procrustes analysis to give a rigid transformation. I will show applications of the method to MRI data of a variety of anatomic regions and imaging contrasts.

I will then present a methodology to track as well as detect cell divisions from time-lapse phase contrast microscopy movies. It first involves pre-processing to remove imaging artifacts. It then detects as well as tracks cells in mitosis or cytokinesis. The anti-causal connectivity of these trajectories provides the cell divisions. The method was demonstrated with movies from samples of several cell lines.

Time permitting, I will also present some of my more recent research on catadioptric omnidirectional imaging. I will first describe some of the benefits of catadioptric imaging. I will then present various imaging optimizations.

About the speaker

Stathis Hadjidemetriou received a B.Eng (Honors) in Electrical Engineering from McGill University in Montreal and an M.Sc. in Electrical Engineering from Columbia University in the City of New York. He received his Ph.D. in computer science also from Columbia University. His thesis was in the fields of image analysis and computer vision.

As post-doctoral fellow at Yale University and as research scientist at University hospitals he specialized in bio-medical image analysis. He has worked on image analysis for biological microscopy related to cancer. He has also worked on organ level biomedical MRI for neurological conditions of the brain as well as for extending the use of quantitative MRI for the whole body.

The methodologies he developed have been on the reconstruction and restoration of MRI data to remove imaging artifacts, the registration of multi-contrast MRI data, as well as on image analysis. The image analysis has included segmentation, motion tracking both for microscopy and torso MRI, as well as for MRI atlas computation.

He is currently associate professor at the Applied Information Technologies (AIT) program at CIIM. He continues the development and application of methodology both for image analysis as well as for more general aspects of artificial intelligence.

He has published numerous research papers in scientific journals and presented his work in numerous scientific conferences. He serves as a reviewer for various international conferences and journals.

He has extensive teaching experience in computer science, electrical engineering and biomedical engineering.

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