Tuesday, March 04, 2025,
15:00-16:00 |
The
Health AI and Data Science (HAD)
Program presents
Simultaneous Partial Volume Correction and Denoising of Clinical and Phantom Brain Dataset Using Deep Learning
Speaker:
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Sanaz Kaviani
I have a PhD in Biomedical Engineering from Université de Montréal, where I focused on enhancing PET brain imaging using deep learning and advanced reconstruction techniques. Currently, as a postdoctoral researcher at Ottawa Hospital and Jubilant, I develop AI-based solutions for PET imaging, including AI-driven denoising and gated parametric mapping for cardiac PET scans.
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Location:
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Virtual via MS Teams. Meeting ID: 236 690 246 000 | Passcode: rC2ui98d
Please contact Emma Brown at emmabrown1@ohri.ca if you would like the meeting link.
NOTE: If you would like to be added to the HAD - Health AI and Data Science team on MS Teams (including the HAD JC seminar mailing list), please join the team using code: owfh55e. If you are external to TOH/OHRI and would like to be added, please email Emma Brown at emmabrown1@ohri.ca.
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Learning outcomes:
- Simultaneous Partial Volume Correction (PVC) and Denoising of Brain PET images.
- Novel deep learning-based PVC method, leveraging Transformer and U-net architectures to enhance PET image quality and quantitative accuracy
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