6 citations · 15 across the 19 of their papers we have counts for
6 papers · 1 filter
Cancer-Net PCa-Data: An Open-Source Benchmark Dataset for Prostate Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data
Hayden Gunraj, Chi-en Amy Tai, Alexander Wong
The recent introduction of synthetic correlated diffusion (CDI) imaging has demonstrated significant potential in the realm of clinical decision support for prostate cancer (PC…
Cancer-Net BCa-S: Breast Cancer Grade Prediction using Volumetric Deep Radiomic Features from Synthetic Correlated Diffusion Imaging
Chi-en Amy Tai, Hayden Gunraj, Alexander Wong
The prevalence of breast cancer continues to grow, affecting about 300,000 females in the United States in 2023. However, there are different levels of severity of breast cancer re…
SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence
Hayden Gunraj, Paul Guerrier, Sheldon Fernandez +1
In electronics manufacturing, solder joint defects are a common problem affecting a variety of printed circuit board components. To identify and correct solder joint defects, the s…
Enhancing Clinical Support for Breast Cancer with Deep Learning Models using Synthetic Correlated Diffusion Imaging
Chi-en Amy Tai, Hayden Gunraj, Nedim Hodzic +3
Breast cancer is the second most common type of cancer in women in Canada and the United States, representing over 25\% of all new female cancer cases. As such, there has been imme…
MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy
Yuhao Chen, Hayden Gunraj, E. Zhixuan Zeng +3
Recently, there has been tremendous interest in industry 4.0 infrastructure to address labor shortages in global supply chains. Deploying artificial intelligence-enabled robotic bi…
Insights into Data through Model Behaviour: An Explainability-driven Strategy for Data Auditing for Responsible Computer Vision Applications
Alexander Wong, Adam Dorfman, Paul McInnis +1
In this study, we take a departure and explore an explainability-driven strategy to data auditing, where actionable insights into the data at hand are discovered through the eyes o…