Brain

Parnianpour, Pedram

 447 447 MaLMIC - Machine Learning in Medical Imaging Consortium

Pedram Parnianpour

Email: parnianp@ualberta.ca
Role: Graduate student
Affiliation: Neuroscience and Mental Health Institute, University of Alberta
Website: https://brainbypedram.com
Data to Share: –
Area(s) for Potential Collaboration: Data-driven disease subtyping and staging
Structural and functional MRI
Applied machine learning
Texture analysis
Multicenter data
Statistical analysis
Modality: MR
Organ: Brain
Disease: Neurological disease
Area of Research: Monitor Disease Progression in ALS

Batarchuk, Viktoriia

 495 495 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: batarchuk.viktoria@gmail.com
Role: Post-doctoral fellow
Affiliation: Lakehead University
Website: Viktoriia Batarchuk@Google Scholar
Area(s) for Potential Collaboration: Multimodality EEG-fMRI approach, generative models for image processing, ML algorithms for EEG recordings, functional MRI, hyperpolarized multinuclear MRI
Modality: MR, Other EEG
Organ: Brain
Disease: Neurological disease
Area of Research: Multimodal imaging integration, advanced image processing using machine learning and generative models approach, multinuclear MRI, functional MRI, molecular imaging

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

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

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

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

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