Think Broadly, Go Global, Act Local

If you think you are too small to make a difference, try spending a night with a mosquito

– African Proverb

IMPACTS

6

Regional Clinical Partners

4

International Partner Institutions

4

Peer Reviewed Publications

10000+

Clincal Imaging Data

OUR SUPPORTERS

  • Effective and reproducible data visualizations, with demos in Python – Kendra Oudyk – COMPASS June 2024

    Title: Effective and reproducible data visualizations, with demos in Python Abstract: This talk explores the principles and practices of data visualization, with demonstrations in Python. We will cover best practices for creating transparent, shareable, and reproducible visualizations, emphasizing the importance of considering human perception when creating visualizations.Key topics include: 1) Data visualization principles and best…

  • How can we explain medical image segmentation models – Dr. Caroline Petitjean – COMPASS May 2024

    Title: How can we explain medical image segmentation models? Abstract: Explainability is a crucial field of AI, and in medical image analysis in particular, to ensure building trust with the clinicians. In computer vision, most of the explainability works have historically focused on image classification, notably to produce saliency maps that highlight the pixels that…

  • Generalizable and democratic AI: from classical techniques to modern neural networks – Dr. Juan Eugenio Iglesias – COMPASS April 2024

    Title: Generalizable and democratic AI: from classical techniques to modern neural networks Abstract: Every year, millions of brain MRI scans are acquired in hospitals, which is a figure considerably larger than the size of any research dataset. Therefore, the ability to analyze such scans could transform neuroimaging research – particularly for underrepresented populations that research-oriented…

  • Continuous Evaluation of Denoising Strategies in fMRI Using fMRIPrep and Nilearn – Dr Hao-Ting Wang – COMPASS Mar 2024

    Title: Continuous Evaluation of Denoising Strategies in fMRI Using fMRIPrep and Nilearn Abstract:  Functional magnetic resonance imaging (fMRI) signal measures changes in neuronal activity over time. The signal can be contaminated with unwanted noise, such as movement, which can impact research results. To fix this, researchers perform two steps before data analysis: standardised preprocessing and customised…

  • Improving Anatomical Plausibility and Auditing Fairness in Deep Segmentation Networks – Dr Enzo Ferrente – COMPASS Feb 2024

    Title: Improving Anatomical Plausibility and Auditing Fairness in Deep Segmentation Networks Abstract: The evolution of deep segmentation networks has empowered the enhancement of extensive medical imaging datasets with automatically generated anatomical segmentation masks. In this talk we will discuss recent methods we proposed to improve anatomical plausibility in deep segmentation networks. By improving anatomical plausibility, we…

  • SPARK 2.0: Application Now Open

    The inaugural SPARK Academy, in collaboration with McMedHacks, supported by McGill University Graduate Mobility Awards and Compute Canada, took place from April 3rd to August 31st, 2023. The program focused on addressing the pressing issue of cancer diagnosis in sub-Saharan Africa (SSA), with an emphasis on preparing trainees to participate in the 2023 MICCAI brain tumor segmentation challenge (BraTS). SPARK 2023…