X-ray

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

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

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.

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

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.

Sajja, Shailaja

 686 1024 MaLMIC - Machine Learning in Medical Imaging Consortium

Email: Shailaja.Sajja@rmp.uhn.ca
Role: Analyst
Affiliation: TECHNA, UHN
Website: https://qipcm.technainstitute.com/
Data to Share: Contact for information
Area(s) for Potential Collaboration: Medical Imaging. Contact for further information.
Modality: CT, X-ray
Organ: Brain, Lung
Disease: Respiratory disease
Area of Research: Currently learning about upcoming areas in medical imaging such as: radiomics, theranostics and others. Prior research was in the domain of dual energy, digital tomosynthesis , cone beam CT and phantoms.

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