A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2342
- Type
- D - Journal article
- DOI
-
10.1007/s10916-017-0859-4
- Title of journal
- Journal of Medical Systems
- Article number
- 20
- First page
- -
- Volume
- 42
- Issue
- 1
- ISSN
- 0148-5598
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2017
- URL
-
https://e-space.mmu.ac.uk/619463/
- 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
-
6
- Research group(s)
-
A - Data Science
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work proposes a novel adaptive deformable model for automatic segmentation of the optic disc and cup capable of capturing shape variation and irregularity. The research addresses existing limitations and is one of three pioneering developments from the EPSRC-DHPA (EP/J50063X/1) funded project with industrial partner Optos. It enabled Optos (jvanhemert@optos.com) to optimise their products for commercialisation. It made us a finalist in the prestigious UK ICT pioneer 2015 competition in the transforming society category. The work led to several external projects funded by Optos, the Academy of Medical Sciences (NAF\R1\180371) and Horizon 2020 ‘ImaginLife’ (Grant No.721537).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -