CT

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

Dammak, Salma

300 300 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: sdammak@uwo.ca
Role: Graduate student
Affiliation: Western University
Website: https://scholar.google.com/citations?hl=en&user=6VdPqmMAAAAJ
Area(s) for Potential Collaboration: N/A
Modality: CT, Other Digital pathology
Organ: Lung, Head and Neck, Other Pancreas
Disease: Cancer
Area of Research: Tools for lung cancer diagnosis and treatment response assessment using machine learning

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

Haider, Masoom

768 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: m.haider@utoronto.ca
Role: MD faculty
Affiliation: University of Toronto, Joint Dept of Medical Imaging, UHN, Sinai Health System
Website: https://www.haiderlab.ca/
Data to Share: OPen to multicenter trial in Porstate Cancer and Pancreatic Cancer with MRI and CT
Area(s) for Potential Collaboration: Interested in collaboration that can provide semantic segmentation of medical images to accelerate radiologist annotation of CT and MRI images (Abdominal and Pelvic). Specifically organ segmentation with CT and MRI, and tumor segmentation. Interested in models that combine imaging with prognostication and prediction. Interested in models that allow for predcitoin and prognostication in the cancer setting
Modality: MR, CT
Organ: Prostate, Liver, Kidney, Pancreas
Disease: Cancer
Area of Research: Imaging biomarker discovery using CT and MRI in abdominal and pelvic malignancies with a focus on pancreatic (CT and MRI) and prostate (MRI) cancers and some work in Renal cell carcinoma and HCC (secondary).

Mattonen, Sarah

1024 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: sarah.mattonen@uwo.ca
Role: PhD faculty
Affiliation: Western University
Website: https://www.bainesimaging.com/dr-sarah-mattonen.html
Data to Share: Contact for information
Area(s) for Potential Collaboration: Machine learning algorithm development and validation, lung cancer surgical outcome prediction, head and neck radiotherapy, oligometastatic disease.
Modality: MR, CT, PET
Organ: Lung, Musculoskeletal, Head and Neck
Disease: Cancer
Area of Research: Translational cancer Imaging, medical image analysis, radiomics, machine learning, radiation therapy.

DeVries, David

1024 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: ddevrie8@uwo.ca
Role: Graduate student
Affiliation: Western University
Website: https://www.bainesimaging.com/
Modality: MR, CT
Organ: Brain
Disease: Cancer
Area of Research: Prediction of Brain Metastasis Response to Radiation Treatment using Imaging

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

Zhang, Euan

300 300 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: euan.zhang@medportal.ca
Role: MD faculty
Affiliation: Hamilton Health Sciences and Health Sciences North
Website: https://docs.google.com/document/d/1mxQUF4vbsiLv72gTNLAArRiPgws8Qc-t0K5lBIcUPLQ/edit?usp=sharing
Data to Share: Can acquire imaging datasets as needed
Area(s) for Potential Collaboration: Provide access to privately owned PACS server.
Provide expertise as a diagnostic neuroradiologist.
Modality: MR, CT, X-ray
Organ: Brain, Lung, Liver, Kidney, Head and Neck, Abdominal and pelvic organs
Disease: Stroke and Cardiovascular, Respiratory disease, Cancer, Neurological disease, Liver disease, Kidney disease
Area of Research: Neuroradiology, Thoracic radiology, Abdominal radiology

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

Baldauf-Lenschen, Felix

909 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: felix@altislabs.com
Role: Industry
Affiliation: Altis Labs, Inc.
Website: https://www.altislabs.com/
Data to Share: >65,000 longitudinal CTs of NSCLC patients with associated clinical information (i.e. diagnostic, treatment history, demographics, outcomes). >33,000 chest x-rays of pneumonia and COVID-19 patients with associated clinical information (demographics, diagnostics, comorbidities, outcomes).
Area(s) for Potential Collaboration: 1) Prognostic imaging biomarker development (solid tumors, cardiology, respiratory diseases, neurology)
2) Annotation software for AI development
Modality: CT, X-ray
Organ: Lung
Disease: Heart disease, Respiratory disease, Cancer, Neurological disease, Liver disease, Kidney disease
Area of Research: Prognostic imaging biomarkers, labeling software development.

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