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- affiliation: University College London, UK
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2020 – today
- 2023
[j83]Antonio Ricciardi, Francesco Grussu, Baris Kanber, Ferran Prados
, Marios C. Yiannakas, Bhavana S. Solanky, Frank Riemer, Xavier Golay, Wallace Brownlee, Olga Ciccarelli, Daniel C. Alexander, Claudia A. M. Gandini Wheeler-Kingshott:
Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset. Frontiers Neuroinformatics 17 (2023)- [j82]Hongxiang Lin, Matteo Figini, Felice D'Arco, Godwin Ogbole, Ryutaro Tanno, Stefano B. Blumberg, Lisa Ronan, Biobele J. Brown, David W. Carmichael, Ikeoluwa Lagunju, Judith Helen Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Low-field magnetic resonance image enhancement via stochastic image quality transfer. Medical Image Anal. 87: 102807 (2023) - [j81]Hanyi Chen, Alexandra L. Young, Neil P. Oxtoby, Frederik Barkhof, Daniel C. Alexander, André Altmann:
Transferability of Alzheimer's disease progression subtypes to an independent population cohort. NeuroImage 271: 120005 (2023) - [j80]Henry F. J. Tregidgo, Sonja Soskic, Juri Althonayan, Chiara Maffei, Koen Van Leemput, Polina Golland, Ricardo Insausti, Garikoitz Lerma-Usabiaga, César Caballero-Gaudes, Pedro M. Paz-Alonso, Anastasia Yendiki, Daniel C. Alexander, Martina Bocchetta, Jonathan D. Rohrer, Juan Eugenio Iglesias:
Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas. NeuroImage 274: 120129 (2023) - [j79]Le Zhang, Ryutaro Tanno, Moucheng Xu, Yawen Huang, Kevin Bronik, Chen Jin, Joseph Jacob, Yefeng Zheng, Ling Shao, Olga Ciccarelli, Frederik Barkhof, Daniel C. Alexander:
Learning from multiple annotators for medical image segmentation. Pattern Recognit. 138: 109400 (2023) - [j78]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Joseph Jacob:
MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations With Limited Labels. IEEE Trans. Medical Imaging 42(10): 2988-2999 (2023) - [c100]Alexandra L. Young, Leon M. Aksman, Daniel C. Alexander, Peter A. Wijeratne:
Subtype and Stage Inference with Timescales. IPMI 2023: 15-26 - [c99]Henry F. J. Tregidgo, Sonja Soskic, Mark D. Olchanyi, Juri Althonayan, Benjamin Billot, Chiara Maffei, Polina Golland, Anastasia Yendiki, Daniel C. Alexander, Martina Bocchetta, Jonathan D. Rohrer, Juan Eugenio Iglesias:
Domain-Agnostic Segmentation of Thalamic Nuclei from Joint Structural and Diffusion MRI. MICCAI (8) 2023: 247-257 - [c98]Tiantian He, Elinor Thompson, Anna Schroder, Neil P. Oxtoby, Ahmed Abdulaal, Frederik Barkhof, Daniel C. Alexander:
A Coupled-Mechanisms Modelling Framework for Neurodegeneration. MICCAI (8) 2023: 459-469 - [i51]Lemuel Puglisi, Frederik Barkhof, Daniel C. Alexander, Geoffrey JM Parker, Arman Eshaghi, Daniele Ravì:
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification. CoRR abs/2302.13057 (2023) - [i50]Yaozhi Lu, Shahab Aslani, An Zhao, Ahmed H. Shahin, David Barber, Mark Emberton, Daniel C. Alexander, Joseph Jacob:
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study. CoRR abs/2303.10789 (2023) - [i49]Hongxiang Lin, Matteo Figini, Felice D'Arco, Godwin Ogbole, Ryutaro Tanno, Stefano B. Blumberg, Lisa Ronan, Biobele J. Brown, David W. Carmichael, Ikeoluwa Lagunju, Judith Helen Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Low-field magnetic resonance image enhancement via stochastic image quality transfer. CoRR abs/2304.13385 (2023) - [i48]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob:
Expectation Maximization Pseudo Labelling for Segmentation with Limited Annotations. CoRR abs/2305.01747 (2023) - [i47]Henry F. J. Tregidgo, Sonja Soskic, Mark D. Olchanyi, Juri Althonayan, Benjamin Billot, Chiara Maffei, Polina Golland, Anastasia Yendiki, Daniel C. Alexander, Martina Bocchetta, Jonathan D. Rohrer, Juan Eugenio Iglesias:
Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI. CoRR abs/2305.03413 (2023) - [i46]Christopher S. Parker, Anna Schroder, Sean C. Epstein, James Cole, Daniel C. Alexander, Hui Zhang:
Rician likelihood loss for quantitative MRI using self-supervised deep learning. CoRR abs/2307.07072 (2023) - [i45]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, Sam M. Janes, Yipeng Hu, Daniel C. Alexander, John R. Hurst, Joseph Jacob:
A data-centric deep learning approach to airway segmentation. CoRR abs/2308.00008 (2023) - [i44]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, Daniel C. Alexander, Joseph Jacob:
A 3D deep learning classifier and its explainability when assessing coronary artery disease. CoRR abs/2308.00009 (2023) - [i43]Tiantian He, Elinor Thompson, Anna Schroder, Neil P. Oxtoby, Ahmed Abdulaal, Frederik Barkhof, Daniel C. Alexander:
A coupled-mechanisms modelling framework for neurodegeneration. CoRR abs/2308.05536 (2023) - [i42]Ahmed H. Shahin, An Zhao, Alexander C. Whitehead, Daniel C. Alexander, Joseph Jacob, David Barber:
CenTime: Event-Conditional Modelling of Censoring in Survival Analysis. CoRR abs/2309.03851 (2023) - [i41]Seunghoi Kim, Henry F. J. Tregidgo, Ahmed K. Eldaly, Matteo Figini, Daniel C. Alexander:
A 3D Conditional Diffusion Model for Image Quality Transfer - An Application to Low-Field MRI. CoRR abs/2311.06631 (2023) - 2022
- [j77]Yaozhi Lu, Shahab Aslani, Mark Emberton, Daniel C. Alexander, Joseph Jacob:
Deep Learning-Based Long Term Mortality Prediction in the National Lung Screening Trial. IEEE Access 10: 34369-34378 (2022) - [j76]Neil P. Oxtoby, Cameron Shand, David M. Cash, Daniel C. Alexander, Frederik Barkhof:
Targeted Screening for Alzheimer's Disease Clinical Trials Using Data-Driven Disease Progression Models. Frontiers Artif. Intell. 5: 660581 (2022) - [j75]Daniele Ravì, Stefano B. Blumberg, Silvia Ingala, Frederik Barkhof, Daniel C. Alexander, Neil P. Oxtoby:
Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia. Medical Image Anal. 75: 102257 (2022) - [j74]Alessia Atzeni, Loïc Peter, Eleanor D. Robinson, Emily Blackburn, Juri Althonayan, Daniel C. Alexander, Juan Eugenio Iglesias:
Deep active learning for suggestive segmentation of biomedical image stacks via optimisation of Dice scores and traced boundary length. Medical Image Anal. 81: 102549 (2022) - [j73]Esther E. Bron, Stefan Klein, Annika Reinke, Janne M. Papma, Lena Maier-Hein, Daniel C. Alexander, Neil P. Oxtoby:
Ten years of image analysis and machine learning competitions in dementia. NeuroImage 253: 119083 (2022) - [c97]Panagiotis Barmpoutis, William Waddingham, Christopher Ross, Hamzeh Kayhanian, Daniel C. Alexander, Marnix Jansen:
Gland segmentation in gastric histology images: detection of intestinal metaplasia. EUSIPCO 2022: 1338-1342 - [c96]Chen Jin, Ryutaro Tanno, Thomy Mertzanidou, Eleftheria Panagiotaki, Daniel C. Alexander:
Learning to Downsample for Segmentation of Ultra-High Resolution Images. ICLR 2022 - [c95]Panagiotis Barmpoutis, Jing Yuan, William Waddingham, Christopher Ross, Hamzeh Kayhanian, Tania Stathaki, Daniel C. Alexander, Marnix Jansen:
Multi-scale Deformable Transformer for the Classification of Gastric Glands: The IMGL Dataset. CaPTion@MICCAI 2022: 24-33 - [c94]Jason P. Lim, Stefano B. Blumberg, Neil Narayan, Sean C. Epstein, Daniel C. Alexander, Marco Palombo, Paddy J. Slator:
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-supervised Machine Learning. CDMRI@MICCAI 2022: 77-88 - [c93]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, Omer Unat, Marcel Veltkamp, Mark G. Jones, Coline H. M. Van Moorsel, David Barber, Joseph Jacob, Daniel C. Alexander:
Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis. MICCAI (8) 2022: 223-233 - [c92]Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander:
Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. MICCAI (6) 2022: 421-431 - [c91]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob:
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-supervised Segmentation. MICCAI (5) 2022: 580-590 - [c90]Ahmed H. Shahin, Joseph Jacob, Daniel C. Alexander, David Barber:
Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data. MIDL 2022: 1057-1074 - [c89]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Stefano B. Blumberg, Frederick J. Wilson, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Joseph Jacob:
Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation. MIDL 2022: 1413-1429 - [i40]Yukun Zhou, Moucheng Xu, Yipeng Hu, Stefano B. Blumberg, An Zhao, Siegfried K. Wagner, Pearse A. Keane, Daniel C. Alexander:
VAFO-Loss: VAscular Feature Optimised Loss Function for Retinal Artery/Vein Segmentation. CoRR abs/2203.06425 (2022) - [i39]Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander:
Progressive Subsampling for Oversampled Data - Application to Quantitative MRI. CoRR abs/2203.09268 (2022) - [i38]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Stefano B. Blumberg, Frederick J. Wilson, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Joseph Jacob:
Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation. CoRR abs/2203.10196 (2022) - [i37]Ahmed H. Shahin, Joseph Jacob, Daniel C. Alexander, David Barber:
Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data. CoRR abs/2203.11391 (2022) - [i36]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, Joseph Jacob:
Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning. CoRR abs/2203.16606 (2022) - [i35]Daniele Ravì, Frederik Barkhof, Daniel C. Alexander, Geoffrey J. M. Parker, Arman Eshaghi:
An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training. CoRR abs/2206.03359 (2022) - [i34]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob:
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation. CoRR abs/2208.04435 (2022) - [i33]Shahab Aslani, Watjana Lilaonitkul, Vaishnavi Gnanananthan, Divya Raj, Bojidar Rangelov, Alexandra L. Young, Yipeng Hu, Paul Taylor, Daniel C. Alexander, Joseph Jacob:
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors. CoRR abs/2208.10320 (2022) - [i32]Jason P. Lim, Stefano B. Blumberg, Neil Narayan, Sean C. Epstein, Daniel C. Alexander, Marco Palombo, Paddy J. Slator:
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning. CoRR abs/2210.02349 (2022) - [i31]Stefano B. Blumberg, Hongxiang Lin, Yukun Zhou, Paddy Slator, Daniel C. Alexander:
An Experiment Design Paradigm using Joint Feature Selection and Task Optimization. CoRR abs/2210.06891 (2022) - [i30]Stefano B. Blumberg, Daniele Ravì, Mou-Cheng Xu, Matteo Figini, Iasonas Kokkinos, Daniel C. Alexander:
Deformably-Scaled Transposed Convolution. CoRR abs/2210.09446 (2022) - 2021
- [j72]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, Joseph Jacob:
A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning. IEEE Access 9: 108873-108888 (2021) - [j71]Damiano Archetti, Alexandra L. Young, Neil P. Oxtoby, Daniel Ferreira, Gustav Mårtensson, Eric Westman, Daniel C. Alexander, Giovanni B. Frisoni, Alberto Redolfi:
Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease. Frontiers Big Data 4: 661110 (2021) - [j70]Peter A. Wijeratne, Eileanoir B. Johnson, Sarah Gregory, Nellie Georgiou-Karistianis, Jane S. Paulsen, Rachael I. Scahill, Sarah J. Tabrizi, Daniel C. Alexander:
A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease. Frontiers Big Data 4: 662200 (2021) - [j69]Alexandra L. Young, Jacob W. Vogel, Leon M. Aksman, Peter A. Wijeratne, Arman Eshaghi, Neil P. Oxtoby, Steven C. R. Williams, Daniel C. Alexander:
Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data. Frontiers Artif. Intell. 4: 613261 (2021) - [j68]Maura Bellio, Dominic Furniss, Neil P. Oxtoby, Sara Garbarino, Nicholas C. Firth, Annemie Ribbens, Daniel C. Alexander, Ann Blandford:
Opportunities and Barriers for Adoption of a Decision-Support Tool for Alzheimer's Disease. ACM Trans. Comput. Heal. 2(4): 32:1-32:19 (2021) - [j67]Paddy J. Slator, Jana Hutter, Razvan V. Marinescu, Marco Palombo, Laurence H. Jackson, Alison Ho, Lucy C. Chappell, Mary A. Rutherford, Joseph V. Hajnal, Daniel C. Alexander:
Data-Driven multi-Contrast spectral microstructure imaging with InSpect: INtegrated SPECTral component estimation and mapping. Medical Image Anal. 71: 102045 (2021) - [j66]Nonie Alexander, Daniel C. Alexander, Frederik Barkhof, Spiros C. Denaxas:
Identifying and evaluating clinical subtypes of Alzheimer's disease in care electronic health records using unsupervised machine learning. BMC Medical Informatics Decis. Mak. 21(1): 343 (2021) - [j65]Ioana Hill, Marco Palombo, Mathieu D. Santin, Francesca Branzoli, Anne-Charlotte Philippe, Demian Wassermann, Marie-Stephane Aigrot, Bruno Stankoff, Anne Baron-Van Evercooren, Mehdi Felfli, Dominique Langui, Hui Zhang, Stéphane Lehéricy, Alexandra Petiet, Daniel C. Alexander, Olga Ciccarelli, Ivana Drobnjak:
Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination. NeuroImage 224: 117425 (2021) - [j64]Ryutaro Tanno, Daniel E. Worrall, Enrico Kaden, Aurobrata Ghosh, Francesco Grussu, Alberto Bizzi, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander:
Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI. NeuroImage 225: 117366 (2021) - [j63]Marco Palombo, Andrada Ianus, Michele Guerreri, Daniel Nunes, Daniel C. Alexander, Noam Shemesh, Hui Zhang:
Corrigendum to "SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI" [Neuroimage 215 (2020), 116835]. NeuroImage 226: 117612 (2021) - [j62]Juan Eugenio Iglesias, Benjamin Billot, Yaël Balbastre, Azadeh Tabari, John Conklin, R. Gilberto González, Daniel C. Alexander, Polina Golland, Brian L. Edlow, Bruce Fischl:
Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast. NeuroImage 237: 118206 (2021) - [j61]Noemi G. Gyori, Christopher A. Clark, Daniel C. Alexander, Enrico Kaden:
On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol. NeuroImage 239: 118303 (2021) - [j60]Alberto De Luca, Andrada Ianus, Alexander Leemans, Marco Palombo, Noam Shemesh, Hui Zhang, Daniel C. Alexander, Markus Nilsson, Martijn Froeling, Geert Jan Biessels, Mauro Zucchelli, Matteo Frigo, Enes Albay, Sara Sedlar, Abib Alimi, Samuel Deslauriers-Gauthier, Rachid Deriche, Rutger Fick, Maryam Afzali, Tomasz Pieciak, Fabian Bogusz, Santiago Aja-Fernández, Evren Özarslan, Derek K. Jones, Haoze Chen, Mingwu Jin, Zhijie Zhang, Fengxiang Wang, Vishwesh Nath, Prasanna Parvathaneni, Jan Morez, Jan Sijbers, Ben Jeurissen, Shreyas Fadnavis, Stefan C. Endres, Ariel Rokem, Eleftherios Garyfallidis, Irina Sánchez, Vesna Prchkovska, Paulo Rodrigues, Bennett A. Landman, Kurt G. Schilling:
On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO challenge. NeuroImage 240: 118367 (2021) - [j59]Andrada Ianus, Daniel C. Alexander, Hui Zhang, Marco Palombo:
Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study. NeuroImage 241: 118424 (2021) - [j58]Baris Kanber, Jasper M. Morrow, Uros Klickovic, Stephen J. Wastling, Sachit Shah, Pietro Fratta, Amy R. McDowell, Matt G. Hall, Chris A. Clark, Francesco Muntoni, Mary M. Reilly, Michael G. Hanna, Daniel C. Alexander, Tarek A. Yousry, John S. Thornton:
Musclesense: a Trained, Artificial Neural Network for the Anatomical Segmentation of Lower Limb Magnetic Resonance Images in Neuromuscular Diseases. Neuroinformatics 19(2): 379-383 (2021) - [j57]Leon M. Aksman, Peter A. Wijeratne, Neil P. Oxtoby, Arman Eshaghi, Cameron Shand, André Altmann, Daniel C. Alexander, Alexandra L. Young:
pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm. SoftwareX 16: 100811 (2021) - [j56]Loïc Peter, Daniel C. Alexander, Caroline Magnain, Juan Eugenio Iglesias:
Uncertainty-Aware Annotation Protocol to Evaluate Deformable Registration Algorithms. IEEE Trans. Medical Imaging 40(8): 2053-2065 (2021) - [c88]Seunghoi Kim, Daniel C. Alexander:
AGCN: Adversarial Graph Convolutional Network for 3D Point Cloud Segmentation. BMVC 2021: 431 - [c87]Panagiotis Barmpoutis, Hamzeh Kayhanian, William Waddingham, Daniel C. Alexander, Marnix Jansen:
Three-dimensional tumour microenvironment reconstruction and tumour-immune interactions' analysis. DICTA 2021: 1-6 - [c86]Peter A. Wijeratne, Daniel C. Alexander:
Learning Transition Times in Event Sequences: The Temporal Event-Based Model of Disease Progression. IPMI 2021: 583-595 - [c85]Hongxiang Lin, Yukun Zhou, Paddy J. Slator, Daniel C. Alexander:
Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts. MICCAI (6) 2021: 44-54 - [c84]Yukun Zhou, Moucheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander:
Learning to Address Intra-segment Misclassification in Retinal Imaging. MICCAI (1) 2021: 482-492 - [i29]Loïc Peter, Daniel C. Alexander, Caroline Magnain, Juan Eugenio Iglesias:
Uncertainty-Aware Annotation Protocol to Evaluate Deformable Registration Algorithms. CoRR abs/2104.01217 (2021) - [i28]Yukun Zhou, Moucheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander:
Learning to Address Intra-segment Misclassification in Retinal Imaging. CoRR abs/2104.12138 (2021) - [i27]Chen Jin, Ryutaro Tanno, Thomy Mertzanidou, Eleftheria Panagiotaki, Daniel C. Alexander:
Learning to Downsample for Segmentation of Ultra-High Resolution Images. CoRR abs/2109.11071 (2021) - [i26]Mou-Cheng Xu, Yukun Zhou, Chen Jin, Stefano B. Blumberg, Frederick J. Wilson, Marius de Groot, Neil P. Oxtoby, Daniel C. Alexander, Joseph Jacob:
MisMatch: Learning to Change Predictive Confidences with Attention for Consistency-Based, Semi-Supervised Medical Image Segmentation. CoRR abs/2110.12179 (2021) - [i25]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, Ryan D. Clay, Finbar Foley, Cassandra Braun, Recep Savas, Carole H. Sudre, Tom Doel, Daniel C. Alexander, Peter A. Wijeratne, David J. Hawkes, Yipeng Hu, John R. Hurst, Joseph Jacob:
Evaluation of automated airway morphological quantification for assessing fibrosing lung disease. CoRR abs/2111.10443 (2021) - [i24]Esther E. Bron, Stefan Klein, Annika Reinke, Janne M. Papma, Lena Maier-Hein, Daniel C. Alexander, Neil P. Oxtoby:
Ten years of image analysis and machine learning competitions in dementia. CoRR abs/2112.07922 (2021) - 2020
- [j55]Yunguan Fu, Nina Montaña Brown, Shaheer U. Saeed, Adrià Casamitjana, Zachary Baum, Rémi Delaunay, Qianye Yang, Alexander Grimwood, Zhe Min, Stefano B. Blumberg, Juan Eugenio Iglesias, Dean C. Barratt, Ester Bonmati, Daniel C. Alexander, Matthew J. Clarkson, Tom Vercauteren, Yipeng Hu:
DeepReg: a deep learning toolkit for medical image registration. J. Open Source Softw. 5(55): 2705 (2020) - [j54]Marco Palombo, Andrada Ianus, Michele Guerreri, Daniel Nunes, Daniel C. Alexander, Noam Shemesh, Hui Zhang:
SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. NeuroImage 215: 116835 (2020) - [j53]Francesco Grussu, Marco Battiston, Jelle Veraart, Torben Schneider, Julien Cohen-Adad, Timothy M. Shepherd, Daniel C. Alexander, Els Fieremans, Dmitry S. Novikov, Claudia A. M. Gandini Wheeler-Kingshott:
Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising. NeuroImage 217: 116884 (2020) - [j52]Ross Callaghan, Daniel C. Alexander, Marco Palombo, Hui Zhang:
ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation. NeuroImage 220: 117107 (2020) - [j51]Lipeng Ning, Elisenda Bonet-Carne, Francesco Grussu, Farshid Sepehrband, Enrico Kaden, Jelle Veraart, Stefano B. Blumberg, Can Son Khoo, Marco Palombo, Iasonas Kokkinos, Daniel C. Alexander, Jaume Coll-Font, Benoit Scherrer, Simon K. Warfield, Suheyla Cetin Karayumak, Yogesh Rathi, Simon Koppers, Leon Weninger, Chantal M. W. Tax:
Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results. NeuroImage 221: 117128 (2020) - [j50]Minh Nguyen, Tong He, Lijun An, Daniel C. Alexander, Jiashi Feng, B. T. Thomas Yeo:
Predicting Alzheimer's disease progression using deep recurrent neural networks. NeuroImage 222: 117203 (2020) - [j49]Kyriaki Mengoudi, Daniele Ravì, Keir X. X. Yong, Silvia Primativo, Ivanna M. Pavisic, Emilie Brotherhood, Kirsty Lu, Jonathan M. Schott, Sebastian J. Crutch, Daniel C. Alexander:
Augmenting Dementia Cognitive Assessment With Instruction-Less Eye-Tracking Tests. IEEE J. Biomed. Health Informatics 24(11): 3066-3075 (2020) - [c83]Moucheng Xu, Neil Oxtoby, Daniel C. Alexander, Joseph Jacob:
Learning To Pay Attention To Mistakes. BMVC 2020 - [c82]Le Zhang, Ryutaro Tanno, Kevin Bronik, Chen Jin, Parashkev Nachev, Frederik Barkhof, Olga Ciccarelli, Daniel C. Alexander:
Learning to Segment When Experts Disagree. MICCAI (1) 2020: 179-190 - [c81]Paddy J. Slator, Jana Hutter, Razvan V. Marinescu, Marco Palombo, Laurence H. Jackson, Alison Ho, Lucy C. Chappell, Mary A. Rutherford, Joseph V. Hajnal, Daniel C. Alexander:
Data-Driven Multi-contrast Spectral Microstructure Imaging with InSpect. MICCAI (6) 2020: 375-385 - [c80]Chen Jin, Ryutaro Tanno, Moucheng Xu, Thomy Mertzanidou, Daniel C. Alexander:
Foveation for Segmentation of Mega-Pixel Histology Images. MICCAI (5) 2020: 561-571 - [c79]Pere Planell-Morell, Madhavi Bajekal, Spiros C. Denaxas, Rosalind Raine, Daniel C. Alexander:
Trajectories of Disease Accumulation Using Electronic Health Records. MIE 2020: 469-473 - [c78]Nonie Alexander, Daniel C. Alexander, Frederik Barkhof, Spiros C. Denaxas:
Using Unsupervised Learning to Identify Clinical Subtypes of Alzheimer's Disease in Electronic Health Records. MIE 2020: 499-503 - [c77]Le Zhang, Ryutaro Tanno, Moucheng Xu, Chen Jin, Joseph Jacob, Olga Cicarrelli, Frederik Barkhof, Daniel C. Alexander:
Disentangling Human Error from Ground Truth in Segmentation of Medical Images. NeurIPS 2020 - [i23]Matteo Figini, Hongxiang Lin, Godwin Ogbole, Felice D'Arco, Stefano B. Blumberg, David W. Carmichael, Ryutaro Tanno, Enrico Kaden, Biobele J. Brown, Ikeoluwa Lagunju, Helen J. Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander:
Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients. CoRR abs/2003.07216 (2020) - [i22]Chen Jin, Ryutaro Tanno, Moucheng Xu, Thomy Mertzanidou, Daniel C. Alexander:
Foveation for Segmentation of Ultra-High Resolution Images. CoRR abs/2007.15124 (2020) - [i21]Mou-Cheng Xu, Neil Oxtoby, Daniel C. Alexander, Joseph Jacob:
Learning To Pay Attention To Mistakes. CoRR abs/2007.15131 (2020) - [i20]Le Zhang, Ryutaro Tanno, Mou-Cheng Xu, Chen Jin, Joseph Jacob, Olga Ciccarelli, Frederik Barkhof, Daniel C. Alexander:
Disentangling Human Error from the Ground Truth in Segmentation of Medical Images. CoRR abs/2007.15963 (2020) - [i19]Peter A. Wijeratne, Daniel C. Alexander:
Learning transition times in event sequences: the Event-Based Hidden Markov Model of disease progression. CoRR abs/2011.01023 (2020) - [i18]Yunguan Fu, Nina Montaña Brown, Shaheer U. Saeed, Adrià Casamitjana, Zachary M. C. Baum, Rémi Delaunay, Qianye Yang, Alexander Grimwood, Zhe Min, Stefano B. Blumberg, Juan Eugenio Iglesias, Dean C. Barratt, Ester Bonmati, Daniel C. Alexander, Matthew J. Clarkson, Tom Vercauteren, Yipeng Hu:
DeepReg: a deep learning toolkit for medical image registration. CoRR abs/2011.02580 (2020) - [i17]Juan Eugenio Iglesias, Benjamin Billot, Yaël Balbastre, Azadeh Tabari, John Conklin, Daniel C. Alexander, Polina Golland, Brian L. Edlow, Bruce Fischl:
Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast. CoRR abs/2012.13340 (2020)
2010 – 2019
- 2019
- [j48]Dafnis Batalle, Jonathan O'Muircheartaigh, Antonios Makropoulos, Christopher J. Kelly, Ralica Dimitrova, Emer J. Hughes, Joseph V. Hajnal, Hui Zhang, Daniel C. Alexander, A. David Edwards, Serena J. Counsell:
Different patterns of cortical maturation before and after 38 weeks gestational age demonstrated by diffusion MRI in vivo. NeuroImage 185: 764-775 (2019) - [j47]Marco Palombo, Daniel C. Alexander, Hui Zhang:
A generative model of realistic brain cells with application to numerical simulation of the diffusion-weighted MR signal. NeuroImage 188: 391-402 (2019) - [j46]Marco Lorenzi, Maurizio Filippone, Giovanni B. Frisoni, Daniel C. Alexander, Sébastien Ourselin:
Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease. NeuroImage 190: 56-68 (2019) - [j45]Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Sebastian J. Crutch, Daniel C. Alexander:
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. NeuroImage 192: 166-177 (2019) - [j44]