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2020 – today
- 2024
[j19]James K. Ruffle
, Robert J. Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev:
Computational limits to the legibility of the imaged human brain. NeuroImage 291: 120600 (2024)- [j18]Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts:
Recent methodological advances in federated learning for healthcare. Patterns 5(6): 101006 (2024) - [c25]Pedro Borges, Virginia Fernandez, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Using MR Physics for Domain Generalisation and Super-Resolution. SASHIMI@MICCAI 2024: 177-186 - [i44]Chayanin Tangwiriyasakul, Pedro Borges, Stefano Moriconi, Paul Wright, Yee H. Mah, James T. Teo, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study. CoRR abs/2404.04025 (2024) - [i43]James K. Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau, Rebekah Rajiah, Faith Lee, Sebastian Brandner, Parashkev Nachev, Harpreet Hyare:
VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI. CoRR abs/2404.15318 (2024) - [i42]Simon Deltadahl, Julian D. Gilbey, Christine van Laer, Nancy Boeckx, Mathie Leers, Tanya Freeman, Laura Aiken, Timothy Farren, Matthew Smith, Mohamad Zeina, BloodCounts Consortium, Concetta Piazzese, Joseph Taylor, Nicholas S. Gleadall, Carola-Bibiane Schönlieb, Suthesh Sivapalaratnam, Michael Roberts, Parashkev Nachev:
Deep Generative Classification of Blood Cell Morphology. CoRR abs/2408.08982 (2024) - 2023
- [j17]Guilherme Pombo, Robert J. Gray, M. Jorge Cardoso, Sébastien Ourselin, Geraint Rees, John Ashburner, Parashkev Nachev:
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models. Medical Image Anal. 84: 102723 (2023) - [j16]Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Petteri Teikari, Ashay Patel, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Latent Transformer Models for out-of-distribution detection. Medical Image Anal. 90: 102967 (2023) - [j15]Ziyu Meng, Rong Guo, Tianyao Wang, Bin Bo, Zengping Lin, Yudu Li, Yibo Zhao, Xin Yu, David J. Lin, Parashkev Nachev, Zhi-Pei Liang, Yao Li:
Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping. IEEE Trans. Biomed. Eng. 70(11): 3147-3155 (2023) - [c24]Mark S. Graham, Walter H. L. Pinaya, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Denoising diffusion models for out-of-distribution detection. CVPR Workshops 2023: 2948-2957 - [c23]Pedro Borges, Virginia Fernandez, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised Heteromodal Physics-Informed Representation of MRI Data: Tackling Data Harmonisation, Imputation and Domain Shift. SASHIMI@MICCAI 2023: 53-63 - [c22]Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright, Petru-Daniel Tudosiu, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models. MICCAI (1) 2023: 446-456 - [c21]Dominic Giles, Robert J. Gray, Chris Foulon, Guilherme Pombo, Tianbo Xu, James K. Ruffle, Hans Rolf Jäger, Manuel Jorge Cardoso, Sébastien Ourselin, Geraint Rees, Ashwani Jha, Parashkev Nachev:
InterSynth: A Semi-Synthetic Framework for Benchmarking Prescriptive Inference from Observational Data. ML4MHD 2023: 172-188 - [i41]Guilherme Pombo, Robert J. Gray, Amy P. K. Nelson, Chris Foulon, John Ashburner, Parashkev Nachev:
Deep Variational Lesion-Deficit Mapping. CoRR abs/2305.17478 (2023) - [i40]Tobias Goodwin-Allcock, Ting Gong, Robert J. Gray, Parashkev Nachev, Hui Zhang:
Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols. CoRR abs/2307.01346 (2023) - [i39]Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright, Petru-Daniel Tudosiu, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised 3D out-of-distribution detection with latent diffusion models. CoRR abs/2307.03777 (2023) - [i38]Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. Da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, XueYan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Generative AI for Medical Imaging: extending the MONAI Framework. CoRR abs/2307.15208 (2023) - [i37]Amy PK Nelson, Joe Mole, Guilherme Pombo, Robert J. Gray, James K. Ruffle, Edgar Chan, Geraint E. Rees, Lisa Cipolotti, Parashkev Nachev:
The minimal computational substrate of fluid intelligence. CoRR abs/2308.07039 (2023) - [i36]James K. Ruffle, Robert J. Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev:
The legibility of the imaged human brain. CoRR abs/2309.07096 (2023) - [i35]James K. Ruffle, Henry C. Watkins, Robert J. Gray, Harpreet Hyare, Michel Thiebaut de Schotten, Parashkev Nachev:
Compressed representation of brain genetic transcription. CoRR abs/2310.16113 (2023) - [i34]M. Jorge Cardoso, Julia Moosbauer, Tessa Sundaram Cook, Barbaros Selnur Erdal, Brad W. Genereaux, Vikash Gupta, Bennett A. Landman, Tiarna Lee, Parashkev Nachev, Elanchezhian Somasundaram, Ronald M. Summers, Khaled Younis, Sébastien Ourselin, Franz Pfister:
RAISE - Radiology AI Safety, an End-to-end lifecycle approach. CoRR abs/2311.14570 (2023) - 2022
- [j14]Walter H. L. Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised brain imaging 3D anomaly detection and segmentation with transformers. Medical Image Anal. 79: 102475 (2022) - [j13]Robert Carruthers, Isabel Straw, James K. Ruffle, Daniel Herron, Amy P. K. Nelson, Danilo Bzdok, Delmiro Fernandez-Reyes, Geraint Rees, Parashkev Nachev:
Representational ethical model calibration. npj Digit. Medicine 5 (2022) - [j12]Amy P. K. Nelson, Robert J. Gray, James K. Ruffle, Henry C. Watkins, Daniel Herron, Nick Sorros, Danil Mikhailov, M. Jorge Cardoso, Sébastien Ourselin, Nick McNally, Bryan Williams, Geraint E. Rees, Parashkev Nachev:
Deep forecasting of translational impact in medical research. Patterns 3(5): 100483 (2022) - [j11]Holger Engleitner, Ashwani Jha, Marta Suarez Pinilla, Amy P. K. Nelson, Daniel Herron, Geraint Rees, Karl J. Friston, Martin Rossor, Parashkev Nachev:
GeoSPM: Geostatistical parametric mapping for medicine. Patterns 3(12): 100656 (2022) - [c20]Petru-Daniel Tudosiu, Walter Hugo Lopez Pinaya, Mark S. Graham, Pedro Borges, Virginia Fernandez, Dai Yang, Jeremy Appleyard, Guido Novati, Disha Mehra, Mike Vella, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Morphology-Preserving Autoregressive 3D Generative Modelling of the Brain. SASHIMI@MICCAI 2022: 66-78 - [c19]Tobias Goodwin-Allcock, Jason D. McEwen, Robert J. Gray, Parashkev Nachev, Hui Zhang:
How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation? CDMRI@MICCAI 2022: 101-112 - [c18]Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F. Da Costa, Virginia Fernandez, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Brain Imaging Generation with Latent Diffusion Models. DGM4MICCAI@MICCAI 2022: 117-126 - [c17]Walter H. L. Pinaya, Mark S. Graham, Robert J. Gray, Pedro F. Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H. Mah, Andrew D. MacKinnon, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models. MICCAI (8) 2022: 705-714 - [c16]Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Transformer-based out-of-distribution detection for clinically safe segmentation. MIDL 2022: 457-476 - [c15]Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Fitting Segmentation Networks on Varying Image Resolutions Using Splatting. MIUA 2022: 271-282 - [d1]Robert J. Gray, Matthew Graham, M. Jorge Cardoso, Sébastien Ourselin, Geraint Rees, Parashkev Nachev:
3d_very_deep_vae. Zenodo, 2022
- [i33]Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Transformer-based out-of-distribution detection for clinically safe segmentation. CoRR abs/2205.10650 (2022) - [i32]Walter H. L. Pinaya, Mark S. Graham, Robert J. Gray, Pedro F. Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H. Mah, Andrew D. MacKinnon, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models. CoRR abs/2206.03461 (2022) - [i31]Stefano Moriconi, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Solid NURBS Conforming Scaffolding for Isogeometric Analysis. CoRR abs/2206.04421 (2022) - [i30]James K. Ruffle, Samia Mohinta, Robert J. Gray, Harpreet Hyare, Parashkev Nachev:
Translating automated brain tumour phenotyping to clinical neuroimaging. CoRR abs/2206.06120 (2022) - [i29]Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Fitting Segmentation Networks on Varying Image Resolutions using Splatting. CoRR abs/2206.06445 (2022) - [i28]Tobias Goodwin-Allcock, Jason D. McEwen, Robert J. Gray, Parashkev Nachev, Hui Zhang:
How can spherical CNNs benefit ML-based diffusion MRI parameter estimation? CoRR abs/2207.00572 (2022) - [i27]Robert Carruthers, Isabel Straw, James K. Ruffle, Daniel Herron, Amy P. K. Nelson, Danilo Bzdok, Delmiro Fernandez-Reyes, Geraint Rees, Parashkev Nachev:
Representational Ethical Model Calibration. CoRR abs/2207.12043 (2022) - [i26]Petru-Daniel Tudosiu, Walter Hugo Lopez Pinaya, Mark S. Graham, Pedro Borges, Virginia Fernandez, Dai Yang, Jeremy Appleyard, Guido Novati, Disha Mehra, Mike Vella, Parashkev Nachev, Sébastien Ourselin, Jorge Cardoso:
Morphology-preserving Autoregressive 3D Generative Modelling of the Brain. CoRR abs/2209.03177 (2022) - [i25]Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F. Da Costa, Virginia Fernandez, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Brain Imaging Generation with Latent Diffusion Models. CoRR abs/2209.07162 (2022) - [i24]Mark S. Graham, Walter H. L. Pinaya, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Denoising Diffusion Models for Out-of-Distribution Detection. CoRR abs/2211.07740 (2022) - 2021
- [c14]Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
An MRF-UNet Product of Experts for Image Segmentation. MIDL 2021: 48-59 - [c13]Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised Brain Anomaly Detection and Segmentation with Transformers. MIDL 2021: 596-617 - [i23]Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Unsupervised Brain Anomaly Detection and Segmentation with Transformers. CoRR abs/2102.11650 (2021) - [i22]Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
An MRF-UNet Product of Experts for Image Segmentation. CoRR abs/2104.05495 (2021) - [i21]Henry C. Watkins, Robert J. Gray, Ashwani Jha, Parashkev Nachev:
An artificial intelligence natural language processing pipeline for information extraction in neuroradiology. CoRR abs/2107.10021 (2021) - [i20]Amy P. K. Nelson, Robert J. Gray, James K. Ruffle, Henry C. Watkins, Daniel Herron, Nick Sorros, Danil Mikhailov, M. Jorge Cardoso, Sébastien Ourselin, Nick McNally, Bryan Williams, Geraint E. Rees, Parashkev Nachev:
Deep forecasting of translational impact in medical research. CoRR abs/2110.08904 (2021) - [i19]Anthony Bourached, Robert J. Gray, Ryan-Rhys Griffiths, Ashwani Jha, Parashkev Nachev:
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion. CoRR abs/2111.12602 (2021) - [i18]Guilherme Pombo, Robert J. Gray, Manuel Jorge Cardoso, Sébastien Ourselin, Geraint Rees, John Ashburner, Parashkev Nachev:
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models. CoRR abs/2111.14923 (2021) - 2020
- [j10]Lluís Guasch, Oscar Calderon Agudo, Meng-Xing Tang, Parashkev Nachev, Michael Warner:
Full-waveform inversion imaging of the human brain. npj Digit. Medicine 3 (2020) - [c12]Mark S. Graham, Carole H. Sudre, Thomas Varsavsky, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, Manuel Jorge Cardoso:
Hierarchical Brain Parcellation with Uncertainty. UNSURE/GRAIL@MICCAI 2020: 23-31 - [c11]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 - [c10]Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner:
Flexible Bayesian Modelling for Nonlinear Image Registration. MICCAI (3) 2020: 253-263 - [c9]Thomas Varsavsky, Mauricio Orbes-Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso:
Test-Time Unsupervised Domain Adaptation. MICCAI (1) 2020: 428-436 - [i17]Petru-Daniel Tudosiu, Thomas Varsavsky, Richard Shaw, Mark S. Graham, Parashkev Nachev, Sébastien Ourselin, Carole H. Sudre, M. Jorge Cardoso:
Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE. CoRR abs/2002.05692 (2020) - [i16]Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner:
Flexible Bayesian Modelling for Nonlinear Image Registration. CoRR abs/2006.02338 (2020) - [i15]Mark S. Graham, Carole H. Sudre, Thomas Varsavsky, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Hierarchical brain parcellation with uncertainty. CoRR abs/2009.07573 (2020) - [i14]Thomas Varsavsky, Mauricio Orbes-Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso:
Test-time Unsupervised Domain Adaptation. CoRR abs/2010.01926 (2020) - [i13]Anthony Bourached, Ryan-Rhys Griffiths, Robert J. Gray, Ashwani Jha, Parashkev Nachev:
Generative Model-Enhanced Human Motion Prediction. CoRR abs/2010.11699 (2020)
2010 – 2019
- 2019
- [j9]Baris Kanber, Parashkev Nachev, Frederik Barkhof, Alberto Calvi, Jorge Cardoso, Rosa Cortese, Ferran Prados, Carole H. Sudre, Carmen Tur, Sébastien Ourselin, Olga Ciccarelli:
High-dimensional detection of imaging response to treatment in multiple sclerosis. npj Digit. Medicine 2 (2019) - [j8]Baris Kanber, Parashkev Nachev, Frederik Barkhof, Alberto Calvi, Jorge Cardoso, Rosa Cortese, Ferran Prados, Carole H. Sudre, Carmen Tur, Sébastien Ourselin, Olga Ciccarelli:
Author Correction: High-dimensional detection of imaging response to treatment in multiple sclerosis. npj Digit. Medicine 2 (2019) - [j7]Parashkev Nachev, Daniel Herron, Nick McNally, Geraint Rees, Bryan Williams:
Redefining the research hospital. npj Digit. Medicine 2 (2019) - [j6]Amy P. K. Nelson, Daniel Herron, Geraint Rees, Parashkev Nachev:
Predicting scheduled hospital attendance with artificial intelligence. npj Digit. Medicine 2 (2019) - [j5]Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Inference of Cerebrovascular Topology With Geodesic Minimum Spanning Trees. IEEE Trans. Medical Imaging 38(1): 225-239 (2019) - [c8]Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre:
Empirical Bayesian Mixture Models for Medical Image Translation. SASHIMI@MICCAI 2019: 1-12 - [c7]Mauricio Orbes-Arteaga, Thomas Varsavsky, Carole H. Sudre, Zach Eaton-Rosen, Lewis J. Haddow, Lauge Sørensen, Mads Nielsen, Akshay Pai, Sébastien Ourselin, Marc Modat, Parashkev Nachev, M. Jorge Cardoso:
Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning. DART/MIL3ID@MICCAI 2019: 54-62 - [c6]Stefano Moriconi, Rafael Rehwald, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Towards Quantifying Neurovascular Resilience. MLMECH/CVII-STENT@MICCAI 2019: 149-157 - [c5]Guilherme Pombo, Robert J. Gray, Thomas Varsavsky, John Ashburner, Parashkev Nachev:
Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning. MICCAI (4) 2019: 429-437 - [i12]Guilherme Pombo, Robert J. Gray, Thomas Varsavsky, John Ashburner, Parashkev Nachev:
Bayesian Volumetric Autoregressive generative models for better semisupervised learning. CoRR abs/1907.11559 (2019) - [i11]Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre:
Empirical Bayesian Mixture Models for Medical Image Translation. CoRR abs/1908.05926 (2019) - [i10]Mauricio Orbes-Arteaga, Thomas Varsavsky, Carole H. Sudre, Zach Eaton-Rosen, Lewis J. Haddow, Lauge Sørensen, Mads Nielsen, Akshay Pai, Sébastien Ourselin, Marc Modat, Parashkev Nachev, Manuel Jorge Cardoso:
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning. CoRR abs/1908.05959 (2019) - [i9]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
A Tool for Super-Resolving Multimodal Clinical MRI. CoRR abs/1909.01140 (2019) - [i8]Anthony Bourached, Parashkev Nachev:
Unsupervised Videographic Analysis of Rodent Behaviour. CoRR abs/1910.11065 (2019) - [i7]Stefano Moriconi, Rafael Rehwald, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Towards Quantifying Neurovascular Resilience. CoRR abs/1910.13200 (2019) - 2018
- [j4]Eli Gibson, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Marc Modat, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren:
NiftyNet: a deep-learning platform for medical imaging. Comput. Methods Programs Biomed. 158: 113-122 (2018) - [c4]Thomas Varsavsky, Zach Eaton-Rosen, Carole H. Sudre, Parashkev Nachev, M. Jorge Cardoso:
PIMMS: Permutation Invariant Multi-modal Segmentation. DLMIA/ML-CDS@MICCAI 2018: 201-209 - [c3]Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Elastic Registration of Geodesic Vascular Graphs. MICCAI (1) 2018: 810-818 - [c2]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
MRI Super-Resolution Using Multi-channel Total Variation. MIUA 2018: 217-228 - [i6]Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
VTrails: Inferring Vessels with Geodesic Connectivity Trees. CoRR abs/1806.03111 (2018) - [i5]Thomas Varsavsky, Zach Eaton-Rosen, Carole H. Sudre, Parashkev Nachev, M. Jorge Cardoso:
PIMMS: Permutation Invariant Multi-Modal Segmentation. CoRR abs/1807.06537 (2018) - [i4]Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Elastic Registration of Geodesic Vascular Graphs. CoRR abs/1809.05499 (2018) - [i3]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
MRI Super-Resolution using Multi-Channel Total Variation. CoRR abs/1810.03422 (2018) - [i2]Parashkev Nachev, Geraint Rees, Richard S. Frackowiak:
Lost in translation. F1000Research 7: 620 (2018) - 2017
- [j3]Katherine Dyke, Sophia E. Pépés, Chen Chen, Soyoung Kim, Hilmar P. Sigurdsson, Amelia Draper, Masud Husain, Parashkev Nachev, Penelope A. Gowland, Peter G. Morris, Stephen R. Jackson:
Comparing GABA-dependent physiological measures of inhibition with proton magnetic resonance spectroscopy measurement of GABA using ultra-high-field MRI. NeuroImage 152: 360-370 (2017) - [c1]Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
VTrails: Inferring Vessels with Geodesic Connectivity Trees. IPMI 2017: 672-684 - [i1]Eli Gibson, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren:
NiftyNet: a deep-learning platform for medical imaging. CoRR abs/1709.03485 (2017) - 2011
- [j2]Parashkev Nachev:
The blind executive. NeuroImage 57(2): 312-313 (2011)
2000 – 2009
- 2008
- [j1]Parashkev Nachev, Elizabeth J. Coulthard, Hans Rolf Jäger, Christopher Kennard, Masud Husain:
Enantiomorphic normalization of focally lesioned brains. NeuroImage 39(3): 1215-1226 (2008)
Coauthor Index
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OpenAlex data
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last updated on 2024-10-17 20:31 CEST by the dblp team
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