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NSERC TII Canada
Research Chair in Biomedical Image Analysis
CANDIDATE PUBLIC PRESENTATIONS
Dr. Mehdi Moradi, MSc, PhD, Candidate for NSERC TII Canada Research Chair in Biomedical Image Analysis
Monday, November 5, 2012
2:30 p.m. Room B450, Health Sciences Building
Ultrasound for tissue typing and guidance of
interventions "Ultrasound is a low
cost and real-time medical imaging modality. However, traditional B-mode images
have proved to be inefficient in detecting and staging pathologies such as
prostate cancer, limiting its role to an anatomical guidance modality in
clinical interventions such as biopsy or brachytherapy. Active solutions (such
as elastography) and passive solutions such as feature extraction from the raw
RF ultrasound signals could augment the abilities of ultrasound in tissue
typing. In this talk, I will report my experience and contributions with three
of these approaches. These are: spectral analysis of spatial segments of RF
ultrasound signals, RF time series analysis, and vibroelastography. "
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Tuesday, November 6, 2012
3:00 p.m. Room B450, Health Sciences Building
Image analysis solutions to enhance prostate
interventions “I will present image
analysis solutions that can improve the delivery of both diagnostic and
therapeutic cancer interventions such as biopsy, brachytherapy and surgery. We
argue that these technologies can provide exceptional opportunities for
clinical translation in treatment and diagnosis of cancer. The central element
of the proposed technologies is a radiological profile of different grades of
the disease and relevant normal tissue, created by data driven machine learning
on multiparametric and multimodality images. Specific examples of technologies
that use this framework will be presented. These include a tissue typing method
based on support vector machine classification applied to the analysis of time
series of RF ultrasound signals, and machine learning on multiparametric MRI
data for target selection in MR-guided biopsy. We also describe the engineering
advances and challenges in the process of combining different imaging
modalities for tissue typing, and describe dynamic elastography imaging as a
solution that can facilitate the fusion of image modalities based on physical tissue
properties. The reported research covers the experience of the speaker at
Queen's University, University of British Columbia, and Harvard Medical
School.”
These events are open to all faculty, staff, students,
and guests.
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