334 citations · 1.2k across the 64 of their papers we have counts for
7 papers · 1 filter
An Ensemble Deep Learning Approach for COVID-19 Severity Prediction Using Chest CT Scans
Sidra Aleem, Mayug Maniparambil, Suzanne Little +2
Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality. We present our findings on COVID-19 severity predictio…
Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets
Sidra Aleem, Teerath Kumar, Suzanne Little +3
Over the years, the paradigm of medical image analysis has shifted from manual expertise to automated systems, often using deep learning (DL) systems. The performance of deep learn…
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts
Carles Garcia-Cabrera, Eric Arazo, Kathleen M. Curran +2
Methods that are resilient to artifacts in the cardiac magnetic resonance imaging (MRI) while performing ventricle segmentation, are crucial for ensuring quality in structural and…
Synthetic data for unsupervised polyp segmentation
Enric Moreu, Kevin McGuinness, Noel E. O'Connor
Deep learning has shown excellent performance in analysing medical images. However, datasets are difficult to obtain due privacy issues, standardization problems, and lack of annot…
A Comparative Study of Existing and New Deep Learning Methods for Detecting Knee Injuries using the MRNet Dataset
David Azcona, Kevin McGuinness, Alan F. Smeaton
This work presents a comparative study of existing and new techniques to detect knee injuries by leveraging Stanford's MRNet Dataset. All approaches are based on deep learning and…
Predicting knee osteoarthritis severity: comparative modeling based on patient's data and plain X-ray images
Jaynal Abedin, Joseph Antony, Kevin McGuinness +4
Knee osteoarthritis (KOA) is a disease that impairs knee function and causes pain. A radiologist reviews knee X-ray images and grades the severity level of the impairments accordin…
Assessing Knee OA Severity with CNN attention-based end-to-end architectures
Marc Górriz, Joseph Antony, Kevin McGuinness +2
This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which i…