Breast

Jabbarpour, Amir

1024 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: ajabbarpour@ohri.ca
Role: Graduate student
Affiliation: Carleton University, The Ottawa Hospital
Website: https://ir.linkedin.com/in/amir-jabbarpour
Data to Share: No data to share ye
Area(s) for Potential Collaboration: Cycle GAN, Radiotherapy, Nuclear Medicine, Medical Image Preprocessing
Modality: MR, CT, PET, SPECT, X-ray
Organ: Prostate, Breast, Brain, Lung
Disease: Respiratory disease, Cancer
Area of Research: AI in Radiotherapy
AI in lung VQ scans for detecting PE

Singh, Paramdeep

412 412 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: paramdeepdoctor@gmail.com
Role: MD faculty
Affiliation: All India Institute of Medical Sciences, Bathinda (India)
Website: https://orcid.org/0000-0003-4226-201X
Data to Share: MRI, CT, Xrays
Area(s) for Potential Collaboration: Radiomics
Modality: MR, CT, X-ray
Organ: Prostate, Breast, Cardiac, Brain, Lung, Musculoskeletal, Kidney & Liver, Head and Neck
Disease: Stroke and Cardiovascular, Respiratory disease, Cancer, Neurological disease, Kidney and Liver disease, Musculoskeletal disease
Area of Research: Medical Imaging, Global Health, Radiology

BĂ©riault, Silvain

768 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email:silvain.beriault@elekta.com
Role: Industry
Affiliation: Elekta
Website: https://www.elekta.com
Data to Share: Contact for information
Area(s) for Potential Collaboration: Motion management and online adaptation in radiotherapy
Modality: MR, CT
Organ: Prostate, Breast, Brain, Lung, Kidney & Liver, Head and Neck
Disease: Cancer
Area of Research: MR-guided adaptive radiotherapy, artificial intelligence, motion management, image registration, auto-contouring, image-to-image translation

Jessica Rodgers

Rodgers, Jessica

578 578 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: jessica.rodgers@queensu.ca
Role: Post-doctoral fellow
Affiliation: Queen’s University
Website: https://www.researchgate.net/profile/Jessica-Rodgers
Area(s) for Potential Collaboration: Processing and analysis of ultrasound images, needle/catheter segmentation, gynecologic imaging, breast applications, and brachytherapy
Modality: Ultrasound
Organ: Prostate, Breast, Gynecologic
Disease: Cancer
Area of Research: Creating clinically translatable tools to improve cancer interventions, including image guidance for radiotherapy of gynecologic and prostate cancers and navigation approaches for breast-conserving surgery.

Martel, Anne

374 374 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: a.martel@utoronto.ca
Role: PhD faculty
Affiliation: Sunnybrook Research Institute / University of Toronto
Website: https://scholar.google.ca/citations?hl=en&user=y7u4Ea8AAAAJ&view_op=list_works&sortby=pubdate
Data to Share: https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=52758117
Area(s) for Potential Collaboration: Computational Pathology, AI algorithm development, Survival prediction, Breast imaging
Modality: MR, X-ray, Optical/Microscopy
Organ: Breast, Liver, Other Hematopathology
Disease: Cancer
Area of Research: Medical image and digital pathology analysis, particularly on applications of machine learning for segmentation, diagnosis, and prediction/prognosis. Co-founder of Pathcore, a software company developing complete workflow solutions for digital pathology.

Fenster, Aaron

400 400 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: afenster@robarts.ca
Role: PhD faculty
Affiliation: Western University
Website: https://www.robarts.ca/research/scientists/fenster_aaron.html
Data to Share: 3D ultrasound and MRI images of the prostate
Area(s) for Potential Collaboration: segmentation, classification, and registration of 2D and 3D ultrasound images.
Modality: Ultrasound
Organ: Prostate, Breast, Liver
Disease: Cancer, Musculoskeletal disease
Area of Research: Image-guided intervention, 3D ultrasound

Stanescu, Teo

400 400 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: teodor.stanescu@rmp.uhn.ca
Role: PhD faculty
Affiliation: Princess Margaret Cancer Centre & University of Toronto
Website: http://www.uhnresearch.ca/researcher/teodor
Data to Share: Image data
Area(s) for Potential Collaboration: Image synthesis (MR/CT)
Data classification and prediction
Disease modelling and prediction of outcomes
Management of image quality
Modality: MR, CT, PET, X-ray
Organ: Prostate, Breast, Cardiac, Brain, Lung, Liver, Kidney
Disease: Cancer
Area of Research: Imaging: diagnosis, treatment planning, treatment guidance, follow-up, QA/QC
Radiation Therapy

William, Wasswa

400 400 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: wwasswa@must.ac.ug
Role: PhD faculty
Affiliation: Mbarara University of Science and Technology
Website: https://www.must.ac.ug/
Area(s) for Potential Collaboration: Artificial Intelligence for Health (AI4H), Data Science, Diagnostic Imaging
Modality: Ultrasound, MR, X-ray, Optical/Microscopy
Organ: Prostate, Breast, Brain
Disease: Stroke and Cardiovascular, Cancer, Kidney disease
Area of Research: Artificial Intelligence, Medical Image Analysis, Digital Health, Machine Learning

Andrews, David

300 300 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: david.andrews@sri.utoronto.ca
Role: PhD faculty
Affiliation: Sunnybrook Research Institute & University of Toronto
Website: http://andrewslab.ca/
Data to Share: Please contact for information
Area(s) for Potential Collaboration: Cancer research, Molecular membrane biology, High-content screening, Automated image analysis, Apoptosis
Modality: Optical/Microscopy
Organ: Breast
Disease: Cancer
Area of Research: Cancer research, Molecular membrane biology, High-content screening, Automated image analysis, Apoptosis

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

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