Low-dose GBCA administration for brain tumour dynamic contrast enhanced MRI: a feasibility study

Autor: Daniel Lewis, Ka-Loh Li, Mueez Waqar, David J. Coope, Omar N. Pathmanaban, Andrew T. King, Ibrahim Djoukhadar, Sha Zhao, Timothy F. Cootes, Alan Jackson, Xiaoping Zhu

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)

Abstract A key limitation of current dynamic contrast enhanced (DCE) MRI techniques is the requirement for full-dose gadolinium-based contrast agent (GBCA) administration. The purpose of this feasibility study was to develop and assess a new low GBCA

Externí odkaz: https://doaj.org/article/7176190d36954bfc8936ef0f28e62558

Defect Classification and Detection Using a Multitask Deep One-Class CNN

Autor: Xinghui Dong, Timothy F. Cootes, Christopher J. Taylor

Publikováno v: IEEE Transactions on Automation Science and Engineering. 19:1719-1730

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b4056ef221f2bf7df756d4e7719bdbcc
https://doi.org/10.1109/tase.2021.3109353

Cam morphology but neither acetabular dysplasia nor pincer morphology is associated with osteophytosis throughout the hip: findings from a cross-sectional study in UK Biobank

Autor: Fiona R. Saunders, Richard M. Aspden, Timothy F. Cootes, G Davey Smith, Claudia Lindner, B.G. Faber, Raja Ebsim, Monika Frysz, Nicholas C. Harvey, Jennifer S. Gregory, Jonathan H Tobias

Publikováno v: Faber, B G, Ebsim, R, Saunders, F R, Frysz, M, Gregory, J S, Aspden, R M, Harvey, N, Smith, G D, Cootes, T, Lindner, C & Tobias, J H 2021, ' Cam morphology but neither acetabular dysplasia nor pincer morphology is associated with osteophytosis throughout the hip: findings from a cross-sectional study in UK Biobank ', Osteoarthritis and Cartilage, vol. 29, no. 11, pp. 1521-1529 . https://doi.org/10.1016/j.joca.2021.08.002
Faber, B G, Frysz, M R, Davey Smith, G, Tobias, J H & al., E 2021, ' Cam morphology but neither acetabular dysplasia nor pincer morphology is associated with osteophytosis throughout the hip : findings from a cross-sectional study in UK Biobank ', Osteoarthritis and Cartilage, vol. 29, no. 11, pp. 1521-1529 . https://doi.org/10.1016/j.joca.2021.08.002
Osteoarthritis and Cartilage

Objectives To examine whether acetabular dysplasia (AD), cam and/or pincer morphology are associated with radiographic hip osteoarthritis (rHOA) and hip pain in UK Biobank (UKB) and, if so, what distribution of osteophytes is observed.DesignParticipa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8dfa5ab992a47c9bde72228c251ff680
https://doi.org/10.1016/j.joca.2021.08.002

Quantification of fat fraction in subchondral bone marrow in knee osteoarthritis using Dixon MRI and image registration

Autor: Henry Noorveriandi, Timothy F Cootes, Matthew J Parkes, David T Felson, Terence W O'Neill, Richard Hodgson

Publikováno v: Noorveriandi, H, Cootes, T F, Parkes, M J, Felson, D T, O'Neill, T W & Hodgson, R 2022, ' Quantification of fat fraction in subchondral bone marrow in knee osteoarthritis using Dixon MRI and image registration ', Osteoarthritis Imaging . https://doi.org/10.1016/j.ostima.2022.100067

ObjectivesTo evaluate fat fraction of subchondral bone marrow oedema-like lesions (BMLs) and nearby marrow in knee osteoarthritis (OA) using Dixon MR imaging and to compare conventional volume measurements of BML change with an alternative technique

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be35a7f3dc3b2051b781c9b5c1de0a9e
https://www.research.manchester.ac.uk/portal/en/publications/quantification-of-fat-fraction-in-subchondral-bone-marrow-in-knee-osteoarthritis-using-dixon-mri-and-image-registration(a1f86fe9-f907-446f-baaf-8e5bf70c7865).html

Defect Detection and Classification by Training a Generic Convolutional Neural Network Encoder

Autor: Xinghui Dong, Christopher J. Taylor, Timothy F. Cootes

Publikováno v: Dong, X, Taylor, C J & Cootes, T F 2020, ' Defect Detection and Classification by Training a Generic Convolutional Neural Network Encoder ', IEEE Transactions on Signal Processing, vol. 68, pp. 6055-6069 . https://doi.org/10.1109/TSP.2020.3031188

Non-destructive Testing (NDT) often involves analysing images to identify (rare) defects. We propose a method for locating and classifying abnormalities using Convolutional Neural Networks (CNNs). A particular problem is that it is often difficult to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ec1ecf67597feccb679874005724349
https://doi.org/10.1109/tsp.2020.3031188