Publications
Recent publications by members of the research group. To see a full list of publications for any individual, view their research profile.
- Jaamour, A, Myles, C, Patel, A, Chen, S-J, McMillan, L & Harris-Birtill, D 2023, 'A divide and conquer approach to maximise deep learning mammography classification accuracies', PLoS ONE, vol. 18, no. 5, e0280841. https://doi.org/10.1371/journal.pone.0280841
- Bell, S, Blackwood, JD, Fell, C, Mohammadi, M, Morrison, D, Harris-Birtill, D & Bryson, G 2023, 'An overview of artificial intelligence applications for next-generation gynaecological pathology', Diagnostic Histopathology, vol. 29, no. 10, pp. 442-449. https://doi.org/10.1016/j.mpdhp.2023.07.002
- Fell, C, Mohammadi, M, Morrison, D, Arandjelović, O, Syed, S, Konanahalli, P, Bell, S, Bryson, G, Harrison, DJ & Harris-Birtill, D 2023, 'Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence', PLoS ONE, vol. 18, no. 3, e0282577. https://doi.org/10.1371/journal.pone.0282577
- Morrison, D & Harris-Birtill, DCC 2022, Anonymising pathology data using generative adversarial networks. in JE Tomaszewski, AD Ward & RM (eds), Medical imaging 2022: digital and computational pathology., 1203917, Proceedings of SPIE, vol. 12039, SPIE, Bellingham, WA, SPIE Medical Imaging 2022, San Diego, California, United States, 20/02/22. https://doi.org/10.1117/12.2611803
- Pirzada, P, Morrison, D, Doherty, GH, Dhasmana, DJ & Harris-Birtill, DCC 2022, 'Automated Remote Pulse Oximetry System (ARPOS)', Sensors, vol. 21, no. 13, 4974. https://doi.org/10.3390/s22134974
- Pirzada, P, Wilde, A, Doherty, GH & Harris-Birtill, D 2022, 'Ethics and acceptance of smart homes for older adults', Informatics for Health and Social Care, vol. 47, no. 1, pp. 10-37. https://doi.org/10.1080/17538157.2021.1923500
- Fell, C, Mohammadi, M, Morrison, D, Arandjelovic, O, Caie, P & Harris-Birtill, D 2022, 'Reproducibility of deep learning in digital pathology whole slide image analysis', PLOS Digital Health, vol. 1, no. 12, e0000145. https://doi.org/10.1371/journal.pdig.0000145
- Mohammadi, M, Cooper, J, Arandelovic, O, Fell, CM, Morrison, D, Syed, S, Konanahalli, P, Bell, S, Bryson, G, Harrison, DJ & Harris-Birtill, DCC 2022, 'Weakly supervised learning and interpretability for endometrial whole slide image diagnosis', Experimental Biology and Medicine, vol. 247, no. 22, pp. 2025 - 2037. https://doi.org/10.1177/15353702221126560
- Morrison, D, Harris-Birtill, D & Caie, PD 2021, 'Generative deep learning in digital pathology workflows', The American Journal of Pathology, vol. 191, no. 10, pp. 1717-1723. https://doi.org/10.1016/j.ajpath.2021.02.024
- Rahmat, R, Harris-Birtill, D, Finn, D, Feng, Y, Montgomery, D, Nailon, WH & McLaughlin, S 2021, Radiomics-led monitoring of non-small cell lung cancer patients during radiotherapy. in BW Papież, M Yaqub, J Jiao, AIL Namburete & JA Noble (eds), Medical image understanding and analysis: 25th annual conference, MIUA 2021. Lecture notes in computer science, vol. 12722, Springer, Cham, pp. 532–546, Medical Image Understanding and Analysis, Oxford, United Kingdom, 12/07/21. https://doi.org/10.1007/978-3-030-80432-9_39
- Schrempf, P, Watson, H, Park, E, Pajak, M, MacKinnon, H, Muir, KW, Harris-Birtill, D & O’Neil, AQ 2021, 'Templated text synthesis for expert-guided multi-label extraction from radiology reports', Machine Learning and Knowledge Extraction, vol. 3, no. 2, pp. 299-317. https://doi.org/10.3390/make3020015
- Harris-Birtill, D & Harris-Birtill, R 2021, Understanding computation time: a critical discussion of time as a computational performance metric. in A Misztal, PA Harris & JA Parker (eds), Time in variance. The study of time, vol. 17, Brill, Leiden, pp. 220-248, The 17th triennial conference of the International Society for the Study of Time, California, California, United States, 23/06/19. https://doi.org/10.1163/9789004470170_014
- Stefani, A, Rahmat, R & Harris-Birtill, DCC 2020, Autofocus Net: Auto-focused 3D CNN for Brain Tumour Segmentation. in In Annual Conference on Medical Image Understanding and Analysis: Part of the Communications in Computer and Information Science book series (CCIS). vol. 1248, Springer, pp. 43-55. <https://link.springer.com/chapter/10.1007/978-3-030-52791-4_4>
- Schrempf, P, Watson, H, Mikhael, S, Pajak, M, Falis, M, Lisowska, A, Muir, KW, Harris-Birtill, D & O'Neil, AQ 2020, Paying per-label attention for multi-label extraction from radiology reports. in J Cardoso, H Van Nguyen, N Heller, P Henriques Abreu, I Isgum, W Silva, R Cruz, J Pereira Amorim, V Patel, B Roysam, K Zhou, S Jiang, N Le, K Luu, R Sznitman, V Cheplygina, D Mateus, E Trucco & S Abbasi (eds), Interpretable and Annotation-Efficient Learning for Medical Image Computing: Third International Workshop, iMIMIC 2020, Second International Workshop, MIL3iD 2020, and 5th International Workshop, LABELS 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Image Processing, Computer Vision, Pattern Recognition, and Graphics), vol. 12446 LNCS, Springer, Cham, pp. 277-289, MICCAI Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis 2020, Peru, 8/10/20. https://doi.org/10.1007/978-3-030-61166-8_29