51 citations · 105 across the 29 of their papers we have counts for
29 papers
Exploring the Utility of Self-Supervised Pretraining Strategies for the Detection of Absent Lung Sliding in M-Mode Lung Ultrasound
Blake VanBerlo, Brian Li, Alexander Wong +2
Self-supervised pretraining has been observed to improve performance in supervised learning tasks in medical imaging. This study investigates the utility of self-supervised pretrai…
Recurrence With Correlation Network for Medical Image Registration
Vignesh Sivan, Teodora Vujovic, Raj Ranabhat +3
We present Recurrence with Correlation Network (RWCNet), a medical image registration network with multi-scale features and a cost volume layer. We demonstrate that these architect…
COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound Images
Jessy Song, Ashkan Ebadi, Adrian Florea +3
As the Coronavirus Disease 2019 (COVID-19) continues to impact many aspects of life and the global healthcare systems, the adoption of rapid and effective screening methods to prev…
A Trustworthy Framework for Medical Image Analysis with Deep Learning
Kai Ma, Siyuan He, Pengcheng Xi +3
Computer vision and machine learning are playing an increasingly important role in computer-assisted diagnosis; however, the application of deep learning to medical imaging has cha…
COVID-Net Assistant: A Deep Learning-Driven Virtual Assistant for COVID-19 Symptom Prediction and Recommendation
Pengyuan Shi, Yuetong Wang, Saad Abbasi +1
As the COVID-19 pandemic continues to put a significant burden on healthcare systems worldwide, there has been growing interest in finding inexpensive symptom pre-screening and rec…
Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography
Kai Ma, Pengcheng Xi, Karim Habashy +3
Building AI models with trustworthiness is important especially in regulated areas such as healthcare. In tackling COVID-19, previous work uses convolutional neural networks as the…
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,…
COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos
Hilda Azimi, Ashkan Ebadi, Jessy Song +2
Besides vaccination, as an effective way to mitigate the further spread of COVID-19, fast and accurate screening of individuals to test for the disease is yet necessary to ensure p…
COVID-Net US-X: Enhanced Deep Neural Network for Detection of COVID-19 Patient Cases from Convex Ultrasound Imaging Through Extended Linear-Convex Ultrasound Augmentation Learning
E. Zhixuan Zeng, Adrian Florea, Alexander Wong
As the global population continues to face significant negative impact by the on-going COVID-19 pandemic, there has been an increasing usage of point-of-care ultrasound (POCUS) ima…
ICDBigBird: A Contextual Embedding Model for ICD Code Classification
George Michalopoulos, Michal Malyska, Nicola Sahar +2
The International Classification of Diseases (ICD) system is the international standard for classifying diseases and procedures during a healthcare encounter and is widely used for…
COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data
Hossein Aboutalebi, Maya Pavlova, Mohammad Javad Shafiee +3
Since the World Health Organization declared COVID-19 a pandemic in 2020, the global community has faced ongoing challenges in controlling and mitigating the transmission of the SA…
Improving Classification Model Performance on Chest X-Rays through Lung Segmentation
Hilda Azimi, Jianxing Zhang, Pengcheng Xi +4
Chest radiography is an effective screening tool for diagnosing pulmonary diseases. In computer-aided diagnosis, extracting the relevant region of interest, i.e., isolating the lun…
Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications
Siyuan He, Pengcheng Xi, Ashkan Ebadi +2
Effective representation learning is the key in improving model performance for medical image analysis. In training deep learning models, a compromise often must be made between pe…
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…
COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification
Audrey Chung, Mahmoud Famouri, Andrew Hryniowski +1
The COVID-19 pandemic continues to have a devastating global impact, and has placed a tremendous burden on struggling healthcare systems around the world. Given the limited resourc…
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…
LexSubCon: Integrating Knowledge from Lexical Resources into Contextual Embeddings for Lexical Substitution
George Michalopoulos, Ian McKillop, Alexander Wong +1
Lexical substitution is the task of generating meaningful substitutes for a word in a given textual context. Contextual word embedding models have achieved state-of-the-art results…
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-19 Detection from Chest X-ray Images using Imprinted Weights Approach
Jianxing Zhang, Pengcheng Xi, Ashkan Ebadi +3
The COVID-19 pandemic has had devastating effects on the well-being of the global population. The pandemic has been so prominent partly due to the high infection rate of the virus…
COVID-Net CT-S: 3D Convolutional Neural Network Architectures for COVID-19 Severity Assessment using Chest CT Images
Hossein Aboutalebi, Saad Abbasi, Mohammad Javad Shafiee +1
The health and socioeconomic difficulties caused by the COVID-19 pandemic continues to cause enormous tensions around the world. In particular, this extraordinary surge in the numb…
COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images
Hossein Aboutalebi, Maya Pavlova, Mohammad Javad Shafiee +3
The world is still struggling in controlling and containing the spread of the COVID-19 pandemic caused by the SARS-CoV-2 virus. The medical conditions associated with SARS-CoV-2 in…