2020

Marsden, Mark, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Antony, Joseph ORCID: 0000-0001-6493-7829, Wei, Haolin, Redzic, Milan, Tang, Jian, Hu, Zhilan, Smeaton, Alan F. ORCID: 0000-0003-1028-8389 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2020) Investigating class-level difficulty factors in multi-label classification problems. In: IEEE International Conference on Multimedia & Expo, 6 - 10 July 2020, London, UK. (Virtual). (In Press)

Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Moran, Kieran ORCID: 0000-0003-2015-8967 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2020) Feature learning to automatically assess radiographic knee osteoarthritis severity. In: Nanni, Loris, Brahnam, Sheryl, Brattin, Rick, Ghidoni, Stefano and Jain, Lakhmi, (eds.) Deep Learners and Deep Learner Descriptors for Medical Applications. Intelligent Systems Reference Library (ISRL), 186 . Springer, 9 -93. ISBN 978-3-030-42750-4

2019

Gorriz, Marc, Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Giró-i-Nieto, Xavier ORCID: 0000-0002-9935-5332 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2019) Assessing knee OA severity with CNN attention-based end-to-end architectures. In: International Conference on Medical Imaging with Deep Learning (MIDL 2019), 8 -10 July, 2019, London, UK.

Abedin, Jaynal, Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Moran, Kieran ORCID: 0000-0003-2015-8967, O'Connor, Noel E. ORCID: 0000-0002-4033-9135, Rebholz-Schuhmann, Dietrich and Newell, John (2019) Predicting knee osteoarthritis severity: comparative modeling based on patient's data and plain X-ray images. Nature Scientific Reports, 9 (5761). pp. 1-12. ISSN 2045-2322 (In Press)

2018

Antony, Joseph (2018) Automatic quantification of radiographic knee osteoarthritis severity and associated diagnostic features using deep convolutional neural networks. PhD thesis, Dublin City University.

2017

Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Moran, Kieran ORCID: 0000-0003-2015-8967 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2017) Automatic detection of joints and quantification of knee osteoarthritis severity using convolutional neural networks. In: 13th International Conference on Machine Learning and Data Mining, 15-20 July 2017, New York, USA.. ISBN 978-3-319-62416-7

2016

Antony, Joseph, McGuinness, Kevin ORCID: 0000-0003-1336-6477, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 and Moran, Kieran ORCID: 0000-0003-2015-8967 (2016) Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks. In: 23rd International Conference on Pattern Recognition, 4-8 Dec. 2016, Cancun, Mexico.

2015

Welch, Neil, Moran, Kieran ORCID: 0000-0003-2015-8967, Antony, Joseph, Richter, Chris ORCID: 0000-0001-6017-1520, Marshall, Brendan, Coyle, Joe, Falvey, Eanna and Franklyn-Miller, Andrew ORCID: 0000-0002-7826-2209 (2015) The effects of a free-weight-based resistance training intervention on pain, squat biomechanics and MRI-defined lumbar fat infiltration and functional cross-sectional area in those with chronic low back. BMJ Open Sport Exercise Medicine, 2015 (1). 000050-000050. ISSN 2055-7647

Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Welch, Neil, Coyle, Joe, Franklyn-Miller, Andrew ORCID: 0000-0002-7826-2209, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 and Moran, Kieran ORCID: 0000-0003-2015-8967 (2015) An interactive segmentation tool for quantifying fat in lumbar muscles using axial lumbar-spine MRI. IRBM, 37 (1). pp. 11-22. ISSN 1959-0318

2014

Antony, Joseph ORCID: 0000-0001-6493-7829, McGuinness, Kevin ORCID: 0000-0003-1336-6477, Welch, Neil, Coyle, Joe, Franklyn-Miller, Andrew ORCID: 0000-0002-7826-2209, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 and Moran, Kieran ORCID: 0000-0003-2015-8967 (2014) Fat quantification in MRI-defined lumbar muscles. In: 4th International Conference on Image Processing Theory, Tools and Applications, 14-17 Oct 2014, Paris, France.