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Publications
References and Links to Papers
Explainable Deep Learning for Neuroimaging: A Generalizable Approach for Differential Diagnosis of Brain Diseases
Nighat Bibi, Kathleen M Curran, Jane Courtney
International Conference on Discovery Science
October, 2023
text-guided
Unlearning Spurious Correlations in Chest X-Ray Classification
Misgina Tsighe Hagos, Kathleen M Curran, Brian Mac Namee
International Conference on Discovery Science
October, 2023
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
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
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
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
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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