Building large scale mosiacs from Landsat data. - Lucian Plesea; Joseph Jacob (ACM-GIS, 2000)

Manifold Learning of COPD. - Felix J. S. Bragman; Jamie R. McClelland; Joseph Jacob; John R. Hurst; David J. Hawkes (MICCAI (3), 2017)

Pulmonary Lobe Segmentation With Probabilistic Segmentation of the Fissures and a Groupwise Fissure Prior. - Felix J. S. Bragman; Jamie R. McClelland; Joseph Jacob; John R. Hurst; David J. Hawkes (IEEE Trans. Medical Imaging, 2017)

Tapering analysis of airways with bronchiectasis. - Kin Quan; Rebecca J. Shipley; Ryutaro Tanno; Graeme McPhillips; Vasileios Vavourakis; David Edwards; Joseph Jacob; John R. Hurst; David J. Hawkes (Image Processing, 2018)

Modelling Airway Geometry as Stock Market Data Using Bayesian Changepoint Detection. - Kin Quan; Ryutaro Tanno; Michael Duong; Arjun Nair; Rebecca Shipley; Mark G. Jones; Christopher Brereton; John R. Hurst; David J. Hawkes; Joseph Jacob (MLMI@MICCAI, 2019)

Reproducibility of an airway tapering measurement in CT with application to bronchiectasis. - Kin Quan; Ryutaro Tanno; Rebecca J. Shipley; Jeremy S. Brown; Joseph Jacob; John R. Hurst; David J. Hawkes (CoRR, 2019)

Prevention of Fault Attacks in ASCON Authenticated Cipher Using Cellular Automata. - Joseph Jacob; Jossy Joseph; M. K. Abinshad; Ambili K. N; Jimmy Jose (ACRI, 2020)

Strengthening ACORN Authenticated Cipher with Cellular Automata. - Jossy Joseph; Joseph Jacob; M. K. Abinshad; Ambili K. N; Jimmy Jose (ACRI, 2020)

Learning To Pay Attention To Mistakes. - Moucheng Xu; Neil Oxtoby; Daniel C. Alexander; Joseph Jacob (BMVC, 2020)

Disentangling Human Error from Ground Truth in Segmentation of Medical Images. - Le Zhang 005; Ryutaro Tanno; Moucheng Xu; Chen Jin; Joseph Jacob; Olga Cicarrelli; Frederik Barkhof; Daniel C. Alexander (NeurIPS, 2020)

Disentangling Human Error from the Ground Truth in Segmentation of Medical Images. - Le Zhang 005; Ryutaro Tanno; Mou-Cheng Xu; Chen Jin; Joseph Jacob; Olga Ciccarelli; Frederik Barkhof; Daniel C. Alexander (CoRR, 2020)

The challenges of deploying artificial intelligence models in a rapidly evolving pandemic. - Yipeng Hu; Joseph Jacob; Geoffrey J. M. Parker; David J. Hawkes; John R. Hurst; Danail Stoyanov (Nat. Mach. Intell., 2020)

Learning to Address Intra-segment Misclassification in Retinal Imaging. - Yukun Zhou; Moucheng Xu; Yipeng Hu; Hongxiang Lin; Joseph Jacob; Pearse A. Keane; Daniel C. Alexander (MICCAI (1), 2021)

A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning. - Wing Keung Cheung; Robert Bell; Arjun Nair; Leon J. Menezes; Riyaz Patel; Simon Wan; Kacy Chou; Jiahang Chen; Ryo Torii; Rhodri H. Davies; James C. Moon; Daniel C. Alexander; et al. (IEEE Access, 2021)

MisMatch: Learning to Change Predictive Confidences with Attention for Consistency-Based, Semi-Supervised Medical Image Segmentation. - Mou-Cheng Xu; Yukun Zhou; Chen Jin; Stefano B. Blumberg; Frederick J. Wilson; Marius de Groot; Neil P. Oxtoby; Daniel C. Alexander; Joseph Jacob (CoRR, 2021)

Evaluation of automated airway morphological quantification for assessing fibrosing lung disease. - Ashkan Pakzad; Wing Keung Cheung; Kin Quan; Nesrin Mogulkoc; Coline H. M. Van Moorsel; Brian J. Bartholmai; Hendrik W. Van Es; Alper Ezircan; Frouke Van Beek; Marcel Veltkamp; Ronald A. Karwoski; Tobias Peikert; et al. (CoRR, 2021)

Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors. - Shahab Aslani; Watjana Lilaonitkul; Vaishnavi Gnanananthan; Divya Raj; Bojidar Rangelov; Alexandra L. Young; Yipeng Hu; Paul Taylor; Daniel C. Alexander; Joseph Jacob (MICAD, 2022)

Airway Measurement by Refinement of Synthetic Images Improves Mortality Prediction in Idiopathic Pulmonary Fibrosis. - Ashkan Pakzad; Mou-Cheng Xu; Wing Keung Cheung; Marie Vermant; Tinne Goos; Laurens J. De Sadeleer; Stijn E. Verleden; Wim A. Wuyts; John R. Hurst; Joseph Jacob (DGM4MICCAI@MICCAI, 2022)

Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-supervised Segmentation. - Mou-Cheng Xu; Yukun Zhou; Chen Jin; Marius de Groot; Daniel C. Alexander; Neil P. Oxtoby; Yipeng Hu; Joseph Jacob (MICCAI (5), 2022)

Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis. - An Zhao; Ahmed H. Shahin; Yukun Zhou; Eyjolfur Gudmundsson; Adam Szmul; Nesrin Mogulkoc; Frouke Van Beek; Christopher Brereton; Hendrik W. Van Es; Katarina Pontoppidan; Recep Savas; Timothy Wallis; et al. (MICCAI (8), 2022)

Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data. - Ahmed H. Shahin; Joseph Jacob; Daniel C. Alexander; David Barber (MIDL, 2022)

Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation. - Mou-Cheng Xu; Yukun Zhou; Chen Jin; Stefano B. Blumberg; Frederick J. Wilson; Marius de Groot; Daniel C. Alexander; Neil P. Oxtoby; Joseph Jacob (MIDL, 2022)

Deep Learning-Based Long Term Mortality Prediction in the National Lung Screening Trial. - Yaozhi Lu; Shahab Aslani; Mark Emberton; Daniel C. Alexander; Joseph Jacob (IEEE Access, 2022)

Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Arjun Nair; Daniel C. Alexander; SUMMIT Consortium; et al. (CoRR, 2022)

A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study. - Yaozhi Lu; Shahab Aslani; An Zhao; Ahmed H. Shahin; David Barber; Mark Emberton; Daniel C. Alexander; Joseph Jacob (CoRR, 2023)

Expectation Maximization Pseudo Labelling for Segmentation with Limited Annotations. - Mou-Cheng Xu; Yukun Zhou; Chen Jin; Marius de Groot; Daniel C. Alexander; Neil P. Oxtoby; Yipeng Hu; Joseph Jacob (CoRR, 2023)

A data-centric deep learning approach to airway segmentation. - Wing Keung Cheung; Ashkan Pakzad; Nesrin Mogulkoc; Sarah Needleman; Bojidar Rangelov; Eyjolfur Gudmundsson; An Zhao; Mariam Abbas; Davina McLaverty; Dimitrios Asimakopoulos; Robert Chapman; Recep Savas; et al. (CoRR, 2023)

A 3D deep learning classifier and its explainability when assessing coronary artery disease. - Wing Keung Cheung; Jeremy Kalindjian; Robert Bell; Arjun Nair; Leon J. Menezes; Riyaz Patel; Simon Wan; Kacy Chou; Jiahang Chen; Ryo Torii; Rhodri H. Davies; James C. Moon; et al. (CoRR, 2023)

Learning from multiple annotators for medical image segmentation. - Le Zhang 005; Ryutaro Tanno; Moucheng Xu; Yawen Huang; Kevin Bronik; Chen Jin; Joseph Jacob; Yefeng Zheng 001; Ling Shao 001; Olga Ciccarelli; Frederik Barkhof; Daniel C. Alexander (Pattern Recognit., 2023)

MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations With Limited Labels. - Mou-Cheng Xu; Yukun Zhou; Chen Jin; Marius de Groot; Daniel C. Alexander; Neil P. Oxtoby; Joseph Jacob (IEEE Trans. Medical Imaging, 2023)

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. - Nur Yildirim; Hannah Richardson; Maria Teodora Wetscherek; Junaid Bajwa; Joseph Jacob; Mark Ames Pinnock; Stephen Harris; Daniel Coelho de Castro; Shruthi Bannur; Stephanie L. Hyland; Pratik Ghosh; Mercy Ranjit; et al. (CHI, 2024)

Spectral Transition Evaluation and Heatmap Extraction for Deep Learning Classifiers. - Mehran Azimbagirad; Pardeep Vasudev; Adam Szmul; John McCabe; Shahab Aslani; Niccolò McConnell; Brintha Selvarajah; Amyn Bhamani; Daniel C. Alexander; Joseph Jacob (MICAD, 2024)

Exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms. - John McCabe; Daryl Cheng; Amyn Bhamani; Monica Mullin; Tanya Patrick; Arjun Nair; Sam M. Janes; Carole H. Sudre; Joseph Jacob (FAIMI/EPIMI@MICCAI, 2024)

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Daniel C. Alexander; Arjun Nair; Joseph Jacob (Comput. Medical Imaging Graph., 2024)

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. - Anja Thieme; Abhijith Rajamohan; Benjamin Cooper; Heather Groombridge; Robert Simister; Barney Wong; Nicholas Woznitza; Mark Ames Pinnock; Maria Teodora Wetscherek; Cecily Morrison; Hannah Richardson; Fernando Pérez-García; et al. (CoRR, 2024)

MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels. - Moucheng Xu; Yukun Zhou; Tobias Goodwin-Allcock; Kimia Firoozabadi; Joseph Jacob; Daniel C. Alexander; Paddy J. Slator (CoRR, 2024)

Expectation maximisation pseudo labels. - Moucheng Xu; Yukun Zhou; Chen Jin; Marius de Groot; Daniel C. Alexander; Neil P. Oxtoby; Yipeng Hu; Joseph Jacob (Medical Image Anal., 2024)

CenTime: Event-conditional modelling of censoring in survival analysis. - Ahmed H. Shahin; An Zhao; Alexander C. Whitehead; Daniel C. Alexander; Joseph Jacob; David Barber (Medical Image Anal., 2024)

Evaluation of automated airway morphological quantification for assessing fibrosing lung disease. - Ashkan Pakzad; Wing Keung Cheung; Coline H. M. Van Moorsel; Kin Quan; Nesrin Mogulkoc; Brian J. Bartholmai; H. W. Van Es; Alper Ezircan; Frouke Van Beek; Marcel Veltkamp; Ronald A. Karwoski; T. Peikert; et al. (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2024)

Interpolation-split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance. - Wing Keung Cheung; Ashkan Pakzad; Nesrin Mogulkoc; Sarah Needleman; Bojidar Rangelov; Eyjolfur Gudmundsson; An Zhao; Mariam Abbas; Davina McLaverty; Dimitrios Asimakopoulos; Robert Chapman; Recep Savas; et al. (J. Big Data, 2024)

4D VQ-GAN: Synthesising Medical Scans at Any Time Point for Personalised Disease Progression Modelling of Idiopathic Pulmonary Fibrosis. - An Zhao; Moucheng Xu; Ahmed H. Shahin; Wim A. Wuyts; Mark G. Jones; Joseph Jacob; Daniel C. Alexander (CoRR, 2025)

A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs. - Niccolò McConnell; Pardeep Vasudev; Daisuke Yamada; Daryl Cheng; Mehran Azimbagirad; John McCabe; Shahab Aslani; Ahmed H. Shahin; Yukun Zhou; SUMMIT Consortium; André Altmann; Yipeng Hu; et al. (CoRR, 2025)