Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2380
- Type
- D - Journal article
- DOI
-
10.1109/TMI.2016.2623819
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- -
- First page
- 653
- Volume
- 36
- Issue
- 2
- ISSN
- 0278-0062
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2016
- URL
-
https://e-space.mmu.ac.uk/617805/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
B - Human Centred-Computing
- Citation count
- 20
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the first published efficacy of real-time cervical muscle segmentation. The research has general applicability to neck muscle imaging, in whiplash injury for example, but is proposed as a method for tracking and providing feedback for treatment in patients with cervical dystonia - a painful neurological condition which causes constant muscle contraction. This study enabled collaboration with clinicians at Salford Royal Hospital (christopher.kobylecki@manchester.ac.uk) and together we were able to secure funding from The Dystonia Society (joanne@dystonia.org.uk). We have subsequently generated a strong publication in which we deliver this objective (DOI: 10.1109/JBHI.2020.2964098) as featured in: https://www.mmu.ac.uk/mssm/news-and-events/story/?id=12039
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
