Automated detection, labelling and radiological grading of clinical spinal MRIs

Autor: Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman

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

Abstract Spinal magnetic resonance (MR) scans are a vital tool for diagnosing the cause of back pain for many diseases and conditions. However, interpreting clinically useful information from these scans can be challenging, time-consuming and hard to

Externí odkaz: https://doaj.org/article/62ea267447754e9c93db4dc8a245d74d

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study

Autor: Yuyu Ishimoto, Amir Jamaludin, Cyrus Cooper, Karen Walker-Bone, Hiroshi Yamada, Hiroshi Hashizume, Hiroyuki Oka, Sakae Tanaka, Noriko Yoshimura, Munehito Yoshida, Jill Urban, Timor Kadir, Jeremy Fairbank

Publikováno v: BMC Musculoskeletal Disorders, Vol 21, Iss 1, Pp 1-6 (2020)

Abstract Background MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). However, there is currently no consensus as to how best to classify MRI findings which has hampered the development of robust longitudinal epi

Externí odkaz: https://doaj.org/article/743da13910754e5c8f543dba6fe9d46a

Automated measurement of size of spinal curve in population-based cohorts: validation of a method based on total body dual energy X-ray absorptiometry scans

Autor: Amir Jamaludin, Jeremy Fairbank, Ian Harding, Timor Kadir, Andrew Zisserman, Emma M. Clark

BACKGROUND: Scoliosis is spinal curvature that may progress to require surgical stabilisation. Risk factors for progression are little understood due to lack of population-based research, since radiographs cannot be performed on entire populations du

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f53dd658bf2c1df469477f0d5f7ee5a4
https://doi.org/10.1016/j.bone.2023.116775

Identifying Scoliosis in Population-Based Cohorts: Automation of a Validated Method Based on Total Body Dual Energy X-ray Absorptiometry Scans

Autor: Jeremy Fairbank, Amir Jamaludin, Tim J Peters, Ian Harding, Emma Clark, Andrew Zisserman, Timor Kadir

Publikováno v: Jamaludin, A, Fairbank, J, Harding, I, Kadir, T, Peters, T J, Zisserman, A & Clark, E M 2020, ' Identifying scoliosis in population-based cohorts : automation of a validated method based on total body dual energy X-ray absorptiometry scans ', Calcified Tissue International . https://doi.org/10.1007/s00223-019-00651-9
Calcified Tissue International

Scoliosis is a 3D-torsional rotation of the spine, but risk factors for initiation and progression are little understood. Research is hampered by lack of population-based research since radiographs cannot be performed on entire populations due to the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d631a84124ec955034ff394b2eaf50f
https://doi.org/10.1007/s00223-019-00651-9

Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging

Autor: Amir Jamaludin, Andrew Zisserman, Rhydian Windsor, Timor Kadir

Publikováno v: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030871956
MICCAI (2)

This paper explores the use of self-supervised deep learning in medical imaging in cases where two scan modalities are available for the same subject. Specifically, we use a large publicly-available dataset of over 20,000 subjects from the UK Biobank

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4317cf0d636648fa7e8b6a5cbaa57b9
http://arxiv.org/abs/2107.06652