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References and Links to Papers

Unlearning Spurious Correlations in Chest X-Ray Classification

Misgina Tsighe Hagos, Kathleen M Curran, Brian Mac Namee

International Conference on Discovery Science

October, 2023

Radiomics-based prediction of FIGO grade for placenta accreta spectrum

Helena C. Bartels, Jim O’Doherty, Eric Wolsztynski, David P. Brophy, Roisin MacDermott, David Atallah, Souha Saliba, Constance Young, Paul Downey, Jennifer Donnelly, Tony Geoghegan, Donal J. Brennan & Kathleen M. Curran
European Radiology Experimental

Graphical Abstract

September, 2023

FewSOME: Few Shot Anomaly Detection

Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran

Visual Anomaly and Novelty Detection Workshop at CVPR

January, 2023

Identifying Spurious Correlations and Correcting them with an Explanation-based Learning

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

NeurIPS 2022 workshop on Human-in-the-Loop Learning (HILL)

November, 2022

Impact of Feedback Type on Explanatory Interactive Learning

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

International Symposium on Methodologies for Intelligent Systems, ISMIS 2022

September, 2022

Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts

Carles Garcia-Cabrera, Eric Arazo, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness

STACOM2022 workshop @ MICCAI2022

September, 2022

Bone segmentation in contrast enhanced whole-body computed tomography

Patrick Leydon, Martin O'Connell, Derek Greene, Kathleen M Curran

Biomedical Physics & Engineering Express, Volume 8, Number 5

September, 2022

Integrating feature attribution methods into the loss function of deep learning classifiers

James Callanan, Carles Garcia-Cabrera, Niamh Belton, Gennady Roshchupkin, Kathleen M Curran

24th Irish Machine Vision and Image Processing Conference

Irish Pattern Recognition and Classification Society

August, 2022

Interpretable Identification of Mild Cognitive Impairment Progression Using Stereotactic Surface Projections

Misgina Tsighe Hagos, Ronan P. Killeen, Kathleen M. Curran, Brian Mac Namee, Alzheimer’s Disease Neuroimaging Initiative

Volume 351: PAIS 2022, Pages 153 - 156

July, 2022

D-Dimers as a Predictor of PE in Individuals Undergoing CTPA

A.N. Franciosi, N. McCarthy, B. Gaffney, E. Sweeney, N. O'Connell, J. Duignan, M.P. Keane, D.J. Murphy, K.M. Curran, C. McCarthy (ATS 2022)

January, 2025

Extended D-dimer cut-offs and machine learning for ruling out pulmonary embolism in individuals undergoing computed tomography pulmonary angiography

Alessandro N. Franciosi, Nicholas McCarthy, Brian Gaffney, John Duignan, Eamon Sweeney, Niall O'Connell, Karen Murphy, Fionnuala Ní Áinle, Marcus W. Butler, Jonathan D. Dodd, Michael P. Keane, David J. Murphy, Kathleen M. Curran, Cormac McCarthy (ERJ 2022)

May, 2022

Book Chapter - Impact of Feedback Type on Explanatory Interactive Learning

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee 

ISMIS 2022: Foundations of Intelligent Systems pp 127–137

January 01, 2022

Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability

Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran (MIUA 2021)

July 2021

Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets

Niamh Belton, Aonghus Lawlor, Kathleen M Curran (MIDL 2021)

March 2021

Enterprise imaging and big data: A review from a medical physics perspective

Nicholas McCarthy, Adil Dahlan, Tessa S Cook, Neil O’Hare, Marie-Louise Ryan, Brendan St John, Aonghus Lawlor, Kathleen M Curran

Physica Medica, Volume 83, 2021, Pages 206-220, ISSN 1120-1797, 

March 2021

Interpretability of a deep learning model in the application of cardiac MRI segmentation with an ACDC challenge dataset

Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen Curran

Proceedings Volume 11596, Medical Imaging 2021: Image Processing; 1159636 (2021)

February 2021

Book Chapter - Deep Learning for Magnetic Resonance Images of Gliomas

John J Healy, Kathleen M Curran, Amira Serifovic Trbalic

Deep Learning for Cancer Diagnosis pp 269-300, 2020

September 2020

Bone Segmentation in Contrast Enhanced Whole-Body Computed Tomography

August 13, 2020

Cross-correlation Template Matching for Liver Localisation in Computed Tomography

Patrick Leydon, Martin O'Connell, Derek Greene, Kathleen M Curran

The 2019 Irish Machine Vision and Image Processing Conference (IMVIP 2019), Technological University Dublin, 28-30 August 2019

August 2019

Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

August 30, 2019

Book Chapter - Semi-automatic bone marrow evaluation in PETCT for multiple myeloma

Patrick Leydon, Martin O’Connell, Derek Greene, Kathleen Curran

Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, vol 723. Springer

June 2017

Automatic Bone Marrow Segmentation for PETCT Imaging in Multiple Myeloma

Patrick Leydon, M O’Connell, D Greene, K Curran

Physica Medica Volume 32, Supplement 3, September 2016, Page 242

August 2015

Machine Learning in Prediction of Prostate Brachytherapy Rectal Dose Classes at Day 30

Patrick Leydon, Frank Sullivan, Faisal Jamaluddin, Peter Woulfe, Derek Greene, Kathleen M Curran

The Irish Machine Vision and Image Processing Conference (IMVIP 2015), Dublin, Ireland, 26-28 August 2015

August 2015

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