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Publications

References and Links to Papers

Evaluating UNet Performance in Segmenting Cysts of Diffuse Cystic Lung Disease CT Scans
Katie Noonan, David J. Murphy, Brian Gaffney, Brian Sheehy, Niall McVeigh, Nicholas McCarthy, Alessandro N. Franciosi, Ali Ataya, Nishant Gupta, Francis X. McCormack, Francesco Bonella, Michael P. Keane, Raphael Borie, David A. Lynch, Kathleen M. Curran, Cormac McCarthy
The European Respiratory Society (ERS) 2024

September, 2024

Evaluating the Performance of an Ensemble Neural Network Pipeline in the Classification of Chest CT Scans as Control, Diffuse Cystic Lung Disease and Emphysema
Katie Noonan, David J. Murphy, Brian Gaffney, Brian Sheehy, Niall McVeigh, Nicholas McCarthy, Alessandro N. Franciosi, Ali Ataya, Nishant Gupta, Francis X. McCormack, Francesco Bonella, Michael P. Keane, Raphael Borie, David A. Lynch, Kathleen M. Curran, Cormac McCarthy
American Journal of Respiratory and Critical Care Medicine

May, 2024

Towards a unified approach for unsupervised brain MRI Motion Artefact Detection with few shot Anomaly Detection
Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M Curran
Computerized Medical Imaging and Graphics

April 2024

Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image Segmentation
Sidra Aleem, Fangyijie Wang, Mayug Maniparambil, Eric Arazo, Julia Dietlmeier, Kathleen Curran, Noel E O'Connor, Suzanne Little
CVPR 2024 workshop on Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis (DEF-AI-MIA)

April, 2024

Synthetic positron emission tomography using Conditional-Generative Adversarial Networks for healthy baseline image generation
Patrick Leydon, Caitlin Quinn, Kathleen Curran
Physica Medica: European Journal of Medical Physics

Feburary, 2024

Automatic muscle segmentation on healthy abdominal MRI using nnUNet
Victoria Joppin, Niamh Belton, Marc Adrien Hostin, Marc-Emmanuel Bellemare, Aonghus Lawlor, Kathleen M Curran, Thierry Bège, Catherine Masson, David Bendahan
Medical Imaging with Deep Learning (MIDL) 2024

April, 2024

DyABD: A Dataset and Technique for Synthetically Generating Dynamic Abdominal MRIs with Dual Class and Anatomically Conditioned Diffusion Models
Niamh Belton, Victoria Joppin, Aonghus Lawlor, Kathleen M Curran, Catherine Masson, Thierry Bege, David Bendahan
Medical Imaging with Deep Learning (MIDL) 2024

April, 2024

Cardiac Magnetic Resonance Phase Detection Using Neural Networks
Carles Garcia-Cabrera, Kathleen M Curran, Noel E O'Connor, Kevin McGuinness
The 31st Irish Conference on Artificial Intelligence and Cognitive Science (AICS)

December, 2023

Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer’s Disease from MRI Images
Misgina Tsighe Hagos, Niamh Belton, Ronan P Killeen, Kathleen M Curran, Brian Mac Namee

International Conference on Innovative Techniques and Applications of Artificial Intelligence 2023

November, 2023

Distance-Aware eXplanation Based Learning
Misgina Tsighe Hagos, Niamh Belton, Kathleen M Curran, Brian Mac Namee
IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI)

November, 2023

Cardiac MRI reconstruction from undersampled k-space using double-stream IFFT and a denoising GNA-UNET pipeline
Julia Dietlmeier, Carles Garcia-Cabrera, Anam Hashmi, Kathleen M Curran, Noel E O’Connor
International Workshop on Statistical Atlases and Computational Models of the Heart

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: One-Class Few Shot Anomaly Detection with Siamese Networks
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
International Conference on Pattern Analysis and Intelligent Systems (PAIS) 2022

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
Annual conference on medical image understanding and analysis (MIUA) 2021

July 2021

Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets
Niamh Belton, Aonghus Lawlor, Kathleen M Curran 
Medical Imaging with Deep Learning (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
Patrick Leydon, Martin O’Connell, Derek Greene, Kathleen M Curran
Biomedical Physics & Engineering Express

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

August 2019

Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation
Patrick Leydon, Martin O'Connell, Derek Greene, Kathleen Curran
Technological University Dublin

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

August 2015

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