CT

Ramachandram, Dhanesh

 600 600 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: dhanesh.ramachandram@vectorinstitute.ai
Role: Applied ML Scientist – Health Lead
Affiliation: Vector Institute
Website: https://vectorinstitute.ai
Data to Share: N/A
Area(s) for Potential Collaboration: Medical Image Segmentation
Medical Image Classification
AI deployment
Multimodal Learning
Modality: CT, X-ray, Optical/Microscopy, Other Dermatology, Chronic wounds
Organ: Breast, Brain, Other Skin
Disease: Other Diabetes, Pressure Injuries
Area of Research: Medical Image Segmentation
Medical Image Classification
AI deployment
Multimodal Learning
Deep Survival Analysis

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

Thornhill, Rebecca

 250 250 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: rthornhill@toh.ca
Role: PhD faculty
Affiliation: Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa
Website: https://med.uottawa.ca/radiology/people/thornhill-rebecca
Data to Share: Not directly at present, but welcome opportunity to facilitate discussions with my clinical collaborators
Area(s) for Potential Collaboration: cardiac MRI and 1H/31P MRS of cardiovascular and metabolic disorders; brain/heart and liver/heart interactions; developing approaches for evaluating patient and clinician satisfaction with explanations for ML model decisions in medical imaging in cancer and heart disease
Modality: MR, CT
Organ: Cardiac, Brain, Kidney & Liver
Disease: Heart disease, Stroke and Cardiovascular, Cancer
Area of Research: Magnetic resonance imaging and spectroscopy of cardiovascular and metabolic disorders; radiomics and machine learning in medical imaging, including neuroimaging, oncologic, and cardiovascular applications; developing approaches to explainable ML in medical imaging.

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

Bériault, 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

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