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Publications
References and Links to Papers
Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations
Fangyijie Wang, Kevin Whelan, Guénolé Silvestre, Kathleen M. Curran
MICCAI 2024 Workshop on PerInatal, Preterm and Paediatric Image Analysis
October, 2024
Multiple Sclerosis Diagnosis with Deep Learning and Explainable AI
Nighat Bibi, Jane Courtney, Kathleen M. Curran
Medical Image Understanding and Analysis (MIUA) 2024
July, 2024
Enhancing Multiple Sclerosis Diagnosis with eXplainable AI
Nighat Bibi, Jane Courtney, Kathleen M. Curran
26th Irish Machine Vision and Image Processing Conference (IMVIP) 2024
July, 2024
Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification
Siteng Ma, Honghui Du, Kathleen Curran, Aonghus Lawlor, Ruihai Dong
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2024
October, 2024
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
Office A212,
Health Science Centre,
University College Dublin,
Belfield,
Dublin 4
©2021 by Machine Learning in Medical Imaging and Diagnostics.
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