Diffusion Tensor Orientation Matching for Image Registration. - Kathleen M. Curran; Daniel C. Alexander (Image Processing, 2003)

Similarity Measures for Cardiac Diffusion Tensor Imaging Registration. - Carla Gil; Adrianus J. Bakermans; Baastian J. van Nierop; Gustav J. Strijkers; Hans C. van Assen; Kathleen M. Curran (IMVIP, 2011)

Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images. - Vasanth R. Singan; Thouis R. Jones; Kathleen M. Curran; Jeremy C. Simpson (BMC Bioinform., 2011)

Deep evolution of image representations for handwritten digit recognition. - Alexandros Agapitos; Michael O'Neill 001; Miguel Nicolau; David Fagan; Ahmed Kattan; Anthony Brabazon; Kathleen M. Curran (CEC, 2015)

Semi-automatic Bone Marrow Evaluation in PETCT for Multiple Myeloma. - Patrick Leydon; Martin O'Connell; Derek Greene; Kathleen M. Curran (MIUA, 2017)

Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging. - Diego Pereira Botelho; Kathleen M. Curran; Madeleine M. Lowery (PLoS Comput. Biol., 2019)

Doctoral Colloquium - A Snapshot of the Future: Virtual and Augmented Reality Training for Radiology. - Xuanhui Xu; Eleni E. Mangina; David Kilroy; Kathleen M. Curran; John J. Healy; Abraham G. Campbell (iLRN, 2020)

Bone Segmentation in Contrast Enhanced Whole-Body Computed Tomography. - Patrick Leydon; Martin O'Connell; Derek Greene; Kathleen M. Curran (CoRR, 2020)

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 M. Curran (Image Processing, 2021)

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)

Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets. - Niamh Belton; Aonghus Lawlor; Kathleen M. Curran (CoRR, 2021)

Interpretable Identification of Mild Cognitive Impairment Progression Using Stereotactic Surface Projections. - Misgina Tsighe Hagos; Ronan P. Killeen; Kathleen M. Curran; Brian Mac Namee (PAIS@ECAI, 2022)

Impact of Feedback Type on Explanatory Interactive Learning. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (ISMIS, 2022)

Cardiac Segmentation Using Transfer Learning Under Respiratory Motion Artifacts. - Carles García-Cabrera; Eric Arazo; Kathleen M. Curran; Noel E. O'Connor; Kevin McGuinness (STACOM@MICCAI, 2022)

Identifying Spurious Correlations and Correcting them with an Explanation-based Learning. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (CoRR, 2022)

Cardiac Magnetic Resonance Phase Detection Using Neural Networks. - Carles García-Cabrera; Kathleen M. Curran; Noel E. O'Connor; Kevin McGuinness (AICS, 2023)

FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks. - Niamh Belton; Misgina Tsighe Hagos; Aonghus Lawlor; Kathleen M. Curran (CVPR Workshops, 2023)

Unlearning Spurious Correlations in Chest X-Ray Classification. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (DS, 2023)

Distance-Aware eXplanation Based Learning. - Misgina Tsighe Hagos; Niamh Belton; Kathleen M. Curran; Brian Mac Namee (ICTAI, 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 (SGAI Conf., 2023)

Cardiac MRI Reconstruction from Undersampled K-Space Using Double-Stream IFFT and a Denoising GNA-UNET Pipeline. - Julia Dietlmeier; Carles García-Cabrera; Anam Hashmi; Kathleen M. Curran; Noel E. O'Connor (STACOM@MICCAI, 2023)

FewSOME: Few Shot Anomaly Detection. - Niamh Belton; Misgina Tsighe Hagos; Aonghus Lawlor; Kathleen M. Curran (CoRR, 2023)

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 (CoRR, 2023)

Learning from Exemplary Explanations. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (CoRR, 2023)

Evaluate Fine-tuning Strategies for Fetal Head Ultrasound Image Segmentation with U-Net. - Fangyijie Wang; Guénolé C. M. Silvestre; Kathleen M. Curran (CoRR, 2023)

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 M. Curran; Noel E. O'Connor; Suzanne Little (CVPR Workshops, 2024)

Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach. - Anam Hashmi; Julia Dietlmeier; Kathleen M. Curran; Noel E. O'Connor (EUSIPCO, 2024)

Partition-Based Medical Data Synthesis via Latent Diffusion. - Yannuo Wen; John J. Healy; Kathleen M. Curran (MICAD, 2024)

Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification. - Siteng Ma; Honghui Du; Kathleen M. Curran; Aonghus Lawlor; Ruihai Dong (MICCAI (11), 2024)

Generative Diffusion Model Bootstraps Zero-Shot Classification of Fetal Ultrasound Images in Underrepresented African Populations. - Fangyijie Wang; Kevin M. Whelan; Guénolé C. M. Silvestre; Kathleen M. Curran (PIPPI@MICCAI, 2024)

Synthetic Balancing of Cardiac MRI Datasets. - Carles García-Cabrera; Eric Arazo Sanchez; Enric Moreu; Kathleen M. Curran; Noel E. O'Connor; Kevin McGuinness (MIUA (2), 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 (Comput. Medical Imaging Graph., 2024)

MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head. - Fangyijie Wang; Guénolé C. M. Silvestre; Kathleen M. Curran (CoRR, 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; Guénolé C. M. Silvestre; Kathleen M. Curran; Noel E. O'Connor; Suzanne Little (CoRR, 2024)

Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach. - Anam Hashmi; Julia Dietlmeier; Kathleen M. Curran; Noel E. O'Connor (CoRR, 2024)

Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive Learning Approach. - Niamh Belton; Misgina Tsighe Hagos; Aonghus Lawlor; Kathleen M. Curran (CoRR, 2024)

An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data. - Niamh Belton; Aonghus Lawlor; Kathleen M. Curran (CoRR, 2024)

Segmenting Fetal Head with Efficient Fine-tuning Strategies in Low-resource Settings: an empirical study with U-Net. - Fangyijie Wang; Guénolé C. M. Silvestre; Kathleen M. Curran (CoRR, 2024)

Semi-Supervised Cervical Segmentation on Ultrasound by a Dual Framework for Neural Networks. - Fangyijie Wang; Kathleen M. Curran; Guénolé C. M. Silvestre (ISBI, 2025)

Spatial Aggregation for Semi-supervised Active Learning in 3D Medical Image Segmentation. - Siteng Ma; Honghui Du; Dairui Liu; Kathleen M. Curran; Aonghus Lawlor; Ruihai Dong (MICCAI (8), 2025)

Anatomy-Preserving Counterfactual Edits in Breast MRI via Guided Diffusion. - Bulat Maksudov; Kathleen M. Curran; Alessandra Mileo (Deep-Breath@MICCAI, 2025)

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images. - Fangyijie Wang; Yuan Liang; Sourav Bhattacharjee; Abey Campbell; Kathleen M. Curran; Guénolé C. M. Silvestre (MICCAI (14), 2025)

Differential Diagnosis of Brain Diseases Using Ensemble Learning and Explainable AI. - Nighat Bibi; Kathleen M. Curran; Jane Courtney (VISIGRAPP (2): VISAPP, 2025)

Multi-Level Explainability in Radiomic-based Classification of Multiple Sclerosis and Ischemic Lesions. - Nighat Bibi; Kathleen M. Curran; Ronan P. Killeen; Jane Courtney (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2025)

An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels. - Niamh Belton; Aonghus Lawlor; Kathleen M. Curran (Artif. Intell. Medicine, 2025)

PSFHS challenge report: Pubic symphysis and fetal head segmentation from intrapartum ultrasound images. - Jieyun Bai; Zihao Zhou; Zhanhong Ou; Gregor Köhler; Raphael Stock; Klaus H. Maier-Hein; Marawan Elbatel; Robert Martí; Xiaomeng Li 001; Yaoyang Qiu; Panjie Gou; Gongping Chen; et al. (Medical Image Anal., 2025)

Corrigendum to "PSFHS challenge report: pubic symphysis and fetal head segmentation from intrapartum ultrasound images" [Medical Image Analysis 99 (2025),103353]. - Jieyun Bai; Zihao Zhou; Zhanhong Ou; Gregor Köhler; Raphael Stock; Klaus H. Maier-Hein; Marawan Elbatel; Robert Martí; Xiaomeng Li 001; Yaoyang Qiu; Panjie Gou; Gongping Chen; et al. (Medical Image Anal., 2025)

Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction. - Anam Hashmi; Julia Dietlmeier; Kathleen M. Curran; Noel E. O'Connor (CoRR, 2025)

Towards generating more interpretable counterfactuals via concept vectors: a preliminary study on chest X-rays. - Bulat Maksudov; Kathleen M. Curran; Alessandra Mileo (CoRR, 2025)

Diffusion Model-based Data Augmentation Method for Fetal Head Ultrasound Segmentation. - Fangyijie Wang; Kevin M. Whelan; Félix Balado; Guénolé C. M. Silvestre; Kathleen M. Curran (CoRR, 2025)