Prostate

McIntosh, Chris

 400 400 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: chris.mcintosh@uhn.ca
Role: PhD faculty
Affiliation: University Health Network, and University of Toronto
Website: https://mcintoshml.github.io/
Data to Share: Contact for information
Area(s) for Potential Collaboration: Model development and cross-centre validation
Modality: Ultrasound, MR, CT, X-ray
Organ: Prostate, Breast, Cardiac, Brain, Lung, Head and Neck
Disease: Heart disease, Stroke and Cardiovascular, Respiratory disease, Cancer
Area of Research: Machine Learning, computer vision, medical image segmentation, radiomics, radiation therapy treatment planning, wearables

Lugez, Elodie

 912 1000 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: elodie.lugez@ryerson.ca
Role: PhD faculty
Affiliation: Department of Computer Science, Ryerson University
Website: https://www.ryerson.ca/laboratory-translational-medicine/
Modality: Ultrasound, MR
Organ: Prostate, Breast, Lung, Liver, Kidney, Head and Neck
Disease: Cancer, Liver disease
Area of Research: MR-guided radiotherapy, High-Dose-Rate Brachytherapy, Artificial Intelligence, Image Registration, Segmentation

Tamara Jamaspishvili

Jamaspishvili, Tamara

 1024 681 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: tamara.jamaspishvili@gmail.com
Role: Adjunct Assistant Professor
Affiliation: Queen’s University, Kingston
Website: https://oicr.on.ca/investigators/tamara-jamaspishvili/
Data to Share: prostate cancer images (H&E, IHC)
Area of Research: Developing quantitative approaches for biomarker characterization for genitourinary and other cancers. Highly experienced in digital pathology using machine learning to discover new patterns in cancer phenotypes that might lead to a better prediction of disease outcomes and/or response to treatment. Interested to develop novel ways of measuring tissue-based biomarkers using artificial intelligence to better stratify the patients for disease management in personalized medicine.

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