6 citations · 15 across the 19 of their papers we have counts for
19 papers
Cancer-Net PCa-Gen: Synthesis of Realistic Prostate Diffusion Weighted Imaging Data via Anatomic-Conditional Controlled Latent Diffusion
Aditya Sridhar, Chi-en Amy Tai, Hayden Gunraj +2
In Canada, prostate cancer is the most common form of cancer in men and accounted for 20% of new cancer cases for this demographic in 2022. Due to recent successes in leveraging ma…
COVIDx CXR-4: An Expanded Multi-Institutional Open-Source Benchmark Dataset for Chest X-ray Image-Based Computer-Aided COVID-19 Diagnostics
Yifan Wu, Hayden Gunraj, Chi-en Amy Tai +1
The global ramifications of the COVID-19 pandemic remain significant, exerting persistent pressure on nations even three years after its initial outbreak. Deep learning models have…
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…
Explaining Explainability: Towards Deeper Actionable Insights into Deep Learning through Second-order Explainability
E. Zhixuan Zeng, Hayden Gunraj, Sheldon Fernandez +1
Explainability plays a crucial role in providing a more comprehensive understanding of deep learning models' behaviour. This allows for thorough validation of the model's performan…
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…
A Multi-Institutional Open-Source Benchmark Dataset for Breast Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data
Chi-en Amy Tai, Hayden Gunraj, Alexander Wong
Recently, a new form of magnetic resonance imaging (MRI) called synthetic correlated diffusion (CDI) imaging was introduced and showed considerable promise for clinical decisio…
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…
COVIDx CXR-3: A Large-Scale, Open-Source Benchmark Dataset of Chest X-ray Images for Computer-Aided COVID-19 Diagnostics
Maya Pavlova, Tia Tuinstra, Hossein Aboutalebi +3
After more than two years since the beginning of the COVID-19 pandemic, the pressure of this crisis continues to devastate globally. The use of chest X-ray (CXR) imaging as a compl…
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT Images
Hayden Gunraj, Tia Tuinstra, Alexander Wong
Computed tomography (CT) has been widely explored as a COVID-19 screening and assessment tool to complement RT-PCR testing. To assist radiologists with CT-based COVID-19 screening,…
MEDUSA: Multi-scale Encoder-Decoder Self-Attention Deep Neural Network Architecture for Medical Image Analysis
Hossein Aboutalebi, Maya Pavlova, Hayden Gunraj +4
Medical image analysis continues to hold interesting challenges given the subtle characteristics of certain diseases and the significant overlap in appearance between diseases. In…
COVID-Net MLSys: Designing COVID-Net for the Clinical Workflow
Audrey G. Chung, Maya Pavlova, Hayden Gunraj +7
As the COVID-19 pandemic continues to devastate globally, one promising field of research is machine learning-driven computer vision to streamline various parts of the COVID-19 cli…
Synthetic Correlated Diffusion Imaging Hyperintensity Delineates Clinically Significant Prostate Cancer
Alexander Wong, Hayden Gunraj, Vignesh Sivan +1
Prostate cancer (PCa) is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. The prognosis of PCa is exce…
COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imaging
Alexander MacLean, Saad Abbasi, Ashkan Ebadi +6
The Coronavirus Disease 2019 (COVID-19) pandemic has impacted many aspects of life globally, and a critical factor in mitigating its effects is screening individuals for infections…
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…
COVID-Net CXR-2: An Enhanced Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-ray Images
Maya Pavlova, Naomi Terhljan, Audrey G. Chung +7
As the COVID-19 pandemic continues to devastate globally, the use of chest X-ray (CXR) imaging as a complimentary screening strategy to RT-PCR testing continues to grow given its r…
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse Learning
Hayden Gunraj, Ali Sabri, David Koff +1
The COVID-19 pandemic continues to rage on, with multiple waves causing substantial harm to health and economies around the world. Motivated by the use of CT imaging at clinical in…
COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest CT Images
Hayden Gunraj, Linda Wang, Alexander Wong
The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease,…