Past Events

View past events, presentations/videos and workshops. You can also view previous presentations and video talks from past forum outcomes.

Machine learning for molecular and cellular imaging – Forum, April 22, 2022

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Hartland Jackson will talk about machine learning applied to imaging mass cytometry. Parvin Mousavi will present her work on mass spectrometry applied to real-time intraoperative tumour margin detection. David Andrews will talk about machine learning in high throughput single-cell imaging. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

MaLMIC sponsored machine learning session at ImNO 2022 – Forum, March 23, 2022

1024 767 MaLMIC - Machine Learning in Medical Imaging Consortium

MaLMIC is organizing a machine learning session at ImNO 2022 on Wednesday, March 23, 2022. Alison Noble, a research scientist at University of Oxford, will give a keynote presentation followed by oral and pitch presentations focused on imaging machine learning applications.

Federated learning – Forum, February 18, 2022

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Kam Kafi, Director of Clinical Strategy and Oncology at Imagia will outline the case for federated learning and work underway between Imagia and collaborators. Spyridon Bakas, Assistant Professor at UPenn, will talk about an open platform he has developed to support federated learning for radiology. Aline Talhouk, Assistant Professor at UBC, will talk about privacy issues and introduce the LEAP platform. The presentations will be followed by group discussion on lessons learned, opportunities to collaborate, and sharing of resources.

Machine learning in image-guided intervention – Forum, January 21, 2022

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Derek Cool, an interventional radiologist, discussed the clinical need for machine learning in image-guided intervention. Purang Abolmaesumi and Derek Gillies then presented their research work in the area. The talks were followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Breast Cancer Machine Learning – Forum, November 19, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Dr. Emily Conant, a radiologist from the University of Pennsylvania, gave the lead-off talk and presented the clinical problems and opportunities where machine learning could make significant impact. She was followed by Professor Nico Karssemeijer from Radboud University in the Netherlands. He has developed important algorithms for breast density and is implementing AI approaches to detection of breast cancer. Grey Kuling, PhD candidate from Sunnybrook Research Institute gave the third talk covering the more technical approach of their research work. The talks were followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Lessons Learned in Genomics and Imaging Machine Learning – Forum, October 15, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Phedias Diamandis, a neuropathologist and researcher at UHN, discussed the clinical challenges of classifying brain malignancies and the promise of combining ‘omics with digital morphology to help untangle the substantial heterogeneity in these tumours. This was followed by a talk by Wail Ba-Alawi, an affiliate scientist at Princess Margaret Cancer Centre, on using multi-omics techniques for cancer biomarker discovery, and by Anglin Dent, an MSc student at University of Toronto, who expanded on Phedias’ talk by discussing progress in applying deep learning approaches to define biologically distinct subpopulations in glioblastoma. The talks were followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Immunotherapy Imaging – Forum, September 17, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Annette Hay, a hematologist and clinician-scientist, talked about the ExCELLirate platform followed by two researchers, Tricia Cottrell and Alison Cheung, described their immunotherapy imaging machine learning research. This was followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Alzheimer’s and Small Vessel Disease Imaging – Forum, July 16, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Sandra Black, a neurologist, talked about the clinical perspective followed by two researchers, Maged Goubran and Lyndon Boone, describing their machine learning research in the area. This was followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Cardiac Machine Learning – Forum, June 18, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

James White, a cardiologist, talked about the clinical perspective followed by two researchers, Fatemeh Zabihollahy and Fumin Guo, described their machine learning research in the area. This was followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Reproducibility and good practices for machine learning research – Focused Meeting, May 26, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

On May 21, MaLMIC held an open forum on reproducibility and best practices in machine learning research. Thank you to those that participated in the follow up in-depth meeting on Reproducibility and good practices for machine learning research.

Reproducibility and good practices for machine learning research – Forum, May 21, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Benjamin Haibe-Kains, Chaya Moskowitz and Matt Hemsley talked about reproducibility and good practices in machine learning research. This was followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Pathology – Focused Meeting, April 21, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

On April 16, MaLMIC held an open forum on machine learning in pathology. Thank you to those that participated in the follow up in-depth meeting on machine learning in pathology.

Pathology – Forum, April 16, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Dr. David Berman, a pathologist, discussed unmet clinical needs in pathology machine learning followed by two researchers, Dr. Ali Bashasati and Dr. Chetan Srinidhi, described their machine learning research work in the area. This was followed by discussion focused on opportunities to collaborate and share resources.

Health Data Integration Platforms – Focused Meeting, March 31, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

On March 19, MaLMIC held an open forum on health data integration platforms. Thank you to those who participated on Wednesday, March 31, 2021 at 4 p.m., EDT. in a follow up in-depth meeting on machine learning and health data integration platforms.

Health Data Integration Platforms – Forum, March 19, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Representatives from Quantitative Imaging for Personalized Cancer Medicine, Brain-CODE and Ontario Health Data Platform presented overviews of their data integration platforms. This was followed by discussion focused on opportunities to collaborate and share resources.

Machine Learning and Prostate Cancer – Focused Meeting, Feb. 24, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

On February 19, 2021 the Machine Learning in Medical Imaging Consortium held a forum focused on prostate cancer. Thank you to those who participated in a follow up in-depth meeting on prostate cancer machine learning and data sharing.

Prostate Cancer – Forum, February 19, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Dr. Haider, a radiologist, discussed the prostate cancer unmet clinical need followed by two researchers, Dr. Mousavi and Mr. Orlando, describing their machine learning research work in the area. This was followed by discussion focused on opportunities to collaborate and share resources.

Head and Neck Cancer – Forum, January 22, 2021

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Dr. Lang, a radiation oncologist, discussed the unmet clinical need followed by two researchers, Dr. Mattonen and Mr. Kazmierski, described their machine learning research work in the area. This was followed by discussion focused on opportunities to collaborate and share resources.

Radiomics and Machine Learning in Oncological Medical Imaging – Forum, October 28, 2020

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

The presenters gave short talks highlighting their current research work, their unique approach, datasets they are using, advantages of their strategy, current collaborations and future opportunities.