309 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University College LondonGB21 papers
- Wellcome / EPSRC Centre for Interventional and Surgical SciencesGB8 papers
- King's College LondonGB4 papers
- KU LeuvenBE3 papers
- Hawassa UniversityET2 papers
- Royal London HospitalGB2 papers
- Tel Aviv Sourasky Medical CenterIL2 papers
- Tel Aviv UniversityIL2 papers
- UK Dementia Research InstituteGB2 papers
- Amsterdam UMC Location Vrije Universiteit AmsterdamNL1 paper
- Assistance Publique – Hôpitaux de ParisFR1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
21 papers
Resolving quantitative MRI model degeneracy in self-supervised machine learning
Giulio V. Minore, Louis Dwyer-Hemmings, Timothy J. P. Bray +1
Quantitative MRI (qMRI) estimates tissue properties of interest from measured MRI signals. This process is conventionally achieved by model fitting, whose computational expense lim…
Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM)
Liad Doniza, Mitchel Lee, Tamar Blumenfeld Katzir +5
Quantitative Susceptibility Mapping (QSM) is a technique for measuring magnetic susceptibility of tissues, aiding in the detection of pathologies like traumatic brain injury and mu…
RAIDER: Rapid, anatomy-independent, deep learning-based PDFF and R2* estimation using magnitude-only signals
T. J. P. Bray, G. V. Minore, A. Bainbridge +4
There has been recent interest in the use of magnitude-based fitting methods for estimating proton density fat fraction (PDFF) and R2* from chemical shift-encoded MRI (CSE-MRI) dat…
BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes
Netanell Avisdris, Leo Joskowicz, Brian Dromey +5
Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometr…
Image quality assessment for machine learning tasks using meta-reinforcement learning
Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is per…
A Survey of Zero-shot Generalisation in Deep Reinforcement Learning
Robert Kirk, Amy Zhang, Edward Grefenstette +1
The study of zero-shot generalisation (ZSG) in deep Reinforcement Learning (RL) aims to produce RL algorithms whose policies generalise well to novel unseen situations at deploymen…
Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets
Mengjie Shi, Tianrui Zhao, Simeon J. West +3
Photoacoustic imaging has shown great potential for guiding minimally invasive procedures by accurate identification of critical tissue targets and invasive medical devices (such a…
Voice-assisted Image Labelling for Endoscopic Ultrasound Classification using Neural Networks
Ester Bonmati, Yipeng Hu, Alexander Grimwood +8
Ultrasound imaging is a commonly used technology for visualising patient anatomy in real-time during diagnostic and therapeutic procedures. High operator dependency and low reprodu…
MAGORINO: Magnitude-only fat fraction and R2* estimation with Rician noise modelling
Timothy JP Bray, Alan Bainbridge, Margaret A Hall-Craggs +1
Purpose: Magnitude-based fitting of chemical shift-encoded data enables proton density fat fraction (PDFF) and R2* estimation where complex-based methods fail or when phase data is…
Artificial Intelligence in PET: an Industry Perspective
Arkadiusz Sitek, Sangtae Ahn, Evren Asma +6
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has t…
Volume of hyperintense inflammation (VHI): a deep learning-enabled quantitative imaging biomarker of inflammation load in spondyloarthritis
Carolyna Hepburn, Alexis Jones, Alan Bainbridge +6
Short inversion time inversion recovery (STIR) MRI is widely used in clinical practice to identify and quantify inflammation in axial spondyloarthritis. However, assessment of STIR…
A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections
Fernando Pérez-García, Reuben Dorent, Michele Rizzi +9
Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-th…
Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology
Luis C. Garcia-Peraza-Herrera, Martin Everson, Laurence Lovat +6
Purpose. Early squamous cell neoplasia (ESCN) in the oesophagus is a highly treatable condition. Lesions confined to the mucosal layer can be curatively treated endoscopically. We…
Deep Placental Vessel Segmentation for Fetoscopic Mosaicking
Sophia Bano, Francisco Vasconcelos, Luke M. Shepherd +6
During fetoscopic laser photocoagulation, a treatment for twin-to-twin transfusion syndrome (TTTS), the clinician first identifies abnormal placental vascular connections and laser…
Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection
Kin Quan, Ryutaro Tanno, Michael Duong +7
Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exhibit dilation of the airways. Accurate measurement of dilatation enables assessment of the progression of di…
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…
Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy
Loïc Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir +5
Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syndrome consists in the photo-coagulation of undesired anastomoses located on the placenta which are responsib…
A Log-Euclidean and Total Variation based Variational Framework for Computational Sonography
Jyotirmoy Banerjee, Premal A. Patel, Fred Ushakov +5
We propose a spatial compounding technique and variational framework to improve 3D ultrasound image quality by compositing multiple ultrasound volumes acquired from different probe…
Survivor-complier effects in the presence of selection on treatment, with application to a study of prompt ICU admission
Edward H. Kennedy, Steve Harris, Luke J. Keele
Pre-treatment selection or censoring (`selection on treatment') can occur when two treatment levels are compared ignoring the third option of neither treatment, in `censoring by de…
Direct Estimation of Firing Rates from Calcium Imaging Data
Elad Ganmor, Michael Krumin, Luigi F. Rossi +2
Two-photon imaging of calcium indicators allows simultaneous recording of responses of hundreds of neurons over hours and even days, but provides a relatively indirect measure of t…
Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study
Holger R. Roth, Thomas E. Hampshire, Emma Helbren +4
Potentially precancerous polyps detected with CT colonography (CTC) need to be removed subsequently, using an optical colonoscope (OC). Due to large colonic deformations induced by…