Past Events

Med-ImageNet: Creation of a Compendium of AI-Ready Medical Imaging Data for Deep Learning Analysis – Forum, July 21, 2023

1024 631 MaLMIC - Machine Learning in Medical Imaging Consortium

Artificial Intelligence (AI) applied to medical images has the potential to transform patient care, especially in radiation oncology where radiological imaging is ubiquitous and treatment planning is time consuming.
AI models are data hungry but medical data are often insufficient for many applications. Building foundational models and fine-tuning them for specific medical tasks with only a few data points represents a new avenue of research with high translational potential. However, there is a lack of large compendia of radiological data that are sufficiently curated for building these foundational models.
In this session, the presenters will describe current work on implementing Med-ImageNet, a compendium of radiological images that have been standardised to develop deep learning models, such radiomics predictors or the foundational MedSAM model.

Machine Learning in Computational Neuroimaging- Forum, June 23, 2023

1024 597 MaLMIC - Machine Learning in Medical Imaging Consortium

Enforcing geometry in machine learning for computational neuroimaging
The June forum centers on the vital role of geometric principles in machine learning applications for medical imaging. The first presentation by Ali Khan will address machine learning applications in computational neuroimaging, exploring how geometry can inform the representation of neuroanatomy. The second presentation by Uzair Hussain will explore geometric machine learning in computational diffusion MRI, describing a novel approach for performing machine learning on data modelled as a sphere. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning in Computational Pathology- Forum, May 26, 2023

1024 552 MaLMIC - Machine Learning in Medical Imaging Consortium

For the May forum on machine learning in computational pathology, the first presentation by April Khademi, a researcher, will be about the past, present and future of digital pathology and AI. The second presentation by Phedias Diamandis, a pathologist, will be about approaches to solve implementation challenges of AI in the real world. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning and Precision Health – Forum, April 21, 2023

1024 689 MaLMIC - Machine Learning in Medical Imaging Consortium

For the April forum on machine learning in precision health, the first presentation by Ross Mitchell, a Professor of Medicine and AI scientist at the University of Alberta, will be about AI and Precision Health. The second presentation by Jacob Jaremko a radiologist, entrepreneur and AI scientist, will be about AI augmented ultrasound 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 2023 – Symposium Session, March 23/24, 2023

1024 767 MaLMIC - Machine Learning in Medical Imaging Consortium

MaLMIC is pleased to support three sessions at the ImNO 2023 symposium in London ON on Friday, March 24

Machine Learning in Image Reconstruction – Forum, January 20, 2023

1024 576 MaLMIC - Machine Learning in Medical Imaging Consortium

For the January forum on machine learning in image reconstruction, the first presentation by Ge Wang, a researcher, will be about CT image reconstruction and the second presentation by Charlie Millard, a postdoctoral fellow, will be about MRI image reconstruction. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning in SaRS-COV-2 and COVID Medical Imaging – Forum, November 18, 2022

1024 389 MaLMIC - Machine Learning in Medical Imaging Consortium

Douglas Lee, a cardiologist and clinician scientist, will present his work on machine learning in COVID-related risk analysis using large-scale population data. Simon Graham, a senior scientist, will present his recent work on COVID-related medical imaging. The talks will be followed by a discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Natural Language Processing – Forum, October 28, 2022

1024 545 MaLMIC - Machine Learning in Medical Imaging Consortium

Richard Do, a radiologist, will start the forum with a presentation on natural language processing (NLP) of radiology reports to track metastatic spread. Heidi Hanson, a researcher, will talk about NLP in cancer surveillance. The two presentations will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning in Radiology – Forum, July 15 2022

1000 563 MaLMIC - Machine Learning in Medical Imaging Consortium

Jaron Chong will start the forum with an overview of the state of AI for medical imaging in Canada. The second presentation will be by Alex Bilbily talking about the road to building impactful AI medical devices. The third presentation will be by Benjamin Fine on pre-deployment evaluation. The three talks will be followed by discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

Machine learning in Liquid Biopsy – Forum, June 17 2022

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Alex Wyatt will give a general introduction to liquid biopsy. This will be followed by Eric Zhao talking about his research work using liquid biopsy in head and neck cancer, and Nick Cheng talking about his research work using liquid biopsy for early detection of high-risk breast cancer. The presentations will be followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate and sharing of resources.

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