Past Events

Forum on the Virtual Health Hub – Forum, November 14, 2025

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Listen in to two exciting talks from the Virtual Health Hub, which explored how artificial intelligence and virtual care are transforming access to healthcare.
Dr. Scott Adams examined how AI-assisted imaging is redefining medical imaging and expanding access to advanced diagnostics in underserved communities. He also showcased current projects demonstrating how AI can support a more connected, equitable, and sustainable health system.
Dr. Ivar Mendez focused on how virtual care, when grounded in local partnerships and cultural safety, can improve health outcomes in rural, remote, and Indigenous communities. He highlighted the AI tools developed to enable scalable virtual care solutions across Canada and beyond.

Machine Learning in Neuroimaging – Forum, October 31, 2025

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Listen to this high-impact session on AI for brain imaging that bridged cellular detail and clinical translation. Ahmadreza Attarpour’s talk showcased ACE (Artificial intelligence-based Cartography of Ensembles) and MAPL3 (Mapping Axonal Projections in Light-sheet fluorescence microscopy in 3D): end-to-end deep-learning pipelines that turn teravoxel, cellular-resolution light-sheet datasets from cleared rodent brains into unbiased, brain-wide maps of local neuronal activity and connectivity—at both cellular and laminar scales. The second talk by Mahmoud Salman shifted to the neonatal clinic, introducing a robust deep-learning framework that overcomes poor contrast, motion artifacts, and tiny target structures to precisely segment hippocampal subfields and amygdala sub-nuclei from routine MRI. Together, these talks demonstrated how scalable, generalizable methods are pushing neuroscience forward—from whole-brain mapping at unprecedented scale to reliable quantitative biomarkers of early brain maturation.

Computer- and Robotics- Assisted Cancer Surgery – Forum, September 12, 2025

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Drs. Amoon Jamzad and Laura Connolly shared two cutting-edge perspectives on advancing cancer surgery through robotics and intelligent tools. Laura spoke about her work on integrating AI-enabled robotics and haptic feedback into breast-conserving surgery to improve tumor removal in highly mobile, deformable tissue. She also shared how robotics combined with photoacoustic imaging can inspect resection cavities post-surgery, aiming for a future where no cancer is left behind. Amoon presented his research on applying deep learning to mass spectrometry data—capturing molecular tissue signatures in real time—to help surgeons accurately distinguish healthy from cancerous tissue. Amoon highlighted strategies for making these models trustworthy, explainable, and generalizable, and for translating mass spectrometry into intraoperative and post-resection workflows. Together, these innovations promise to enhance surgical precision, reduce positive margins, and improve patient outcomes.

FULCRUM: A model for the design of educational tools and enabling machine learning/deep learning tools for automated lesion detection

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Glenn Bauman and Katherine Zukotynski spoke at the April MaLMIC forum about FULCRUM, a clinical imaging database they created. It is a database of PSMA PET/CT scans acquired as part of a province-wide prospective study. It is composed of approximately 1000 men with recurrent prostate cancer imaged with 18F-DCFPyL or 18F-PSMA 1007 with centralized expert review, annotation and segmentation of PET-detected recurrent prostate cancer foci. The database is being used to design educational tools and enable machine learning/deep learning tools for automated lesion detection.

Join MaLMIC at the 2025 IGT x ImNO Joint Symposium

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MaLMIC is pleased to support the 2025 IGT x ImNO Joint Symposium in Toronto ON on March 5 and 6, 2025. Throughout the symposium, there will be talks, pitches and posters on AI, deep learning and machine learning.

The Open Health Imaging Foundation – Forum, January 31, 2025

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January 31, 2025
3:00 to 4:30 p.m. Eastern

Gordon Harris and Alireza Sedghi presented information about the Open Health Imaging Foundation (https://ohif.org/), an open source web based medical imaging framework, at the January forum. The presentations were followed by questions and answers about the talks, and discussions focused on lessons learned, opportunities to collaborate, and sharing of data.

Machine learning in radiotherapy applications – Forum, October 25, 2024

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October 25, 2024
3:00 to 4:30 p.m. Eastern

Aly Khalifa and Sanwook Kim presented at the MaLMIC fall forum, hosted by Julia Publicover. The presentations were followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate, and sharing of data.

Using machine learning to address complex challenges in human health – Forum, September 20, 2024

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September 20, 2024
3:00 to 4:30 p.m. Eastern
Elham Dolatabadi and Catherine Stinson presented at the MaLMIC fall forum, hosted by Amber Simpson. The presentations were followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate, and sharing of data.

Enhancing cancer research with quantitative imaging: A deep dive into QIPCM at UHN – Webinar, June 27 2024

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Join us for an engaging webinar on June 27th at 11:30am that showcases the Quantitative Imaging for Personalized Cancer Medicine (QIPCM) program which provides end-to-end testing and analysis support for clinical trials to improve consistency and reliability in clinical trial imaging data.

MaLMIC sponsored machine learning sessions at ImNO 2024 – Symposium Session March 2024

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MaLMIC is pleased to support the ImNO 2024 symposium in Mississauga ON on March 19 and 20, 2024. Here are some of the sessions featuring AI and machine learning:
– Keynote: Anne Martel will talk about AI for medical image analysis: Living with limited data
– Debate: The role of AI in medicine
– Panel: Commercialization of AI-enabled medical imaging technology
Throughout the symposium, there will also be talks, pitches and posters on AI, deep learning and machine learning.
We hope you can join us at ImNO 2024!

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