Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Spatial statistical modelling of capillary non-perfusion in the retina

MacCormick, IJC, Zheng, Y, Czanner, S, Zhao, Y, Diggle, PJ, Harding, SP and Czanner, G (2017) Spatial statistical modelling of capillary non-perfusion in the retina. Scientific Reports, 7. ISSN 2045-2322

[img]
Preview
Text
s41598-017-16620-x.pdf - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

Manual grading of lesions in retinal images is relevant to clinical management and clinical trials, but it is time-consuming and expensive. Furthermore, it collects only limited information - such as lesion size or frequency. The spatial distribution of lesions is ignored, even though it may contribute to the overall clinical assessment of disease severity, and correspond to microvascular and physiological topography. Capillary non-perfusion (CNP) lesions are central to the pathogenesis of major causes of vision loss. Here we propose a novel method to analyse CNP using spatial statistical modelling. This quantifies the percentage of CNP-pixels in each of 48 sectors and then characterises the spatial distribution with goniometric functions. We applied our spatial approach to a set of images from patients with malarial retinopathy, and found it compares favourably with the raw percentage of CNP-pixels and also with manual grading. Furthermore, we were able to quantify a biological characteristic of macular CNP in malaria that had previously only been described subjectively: clustering at the temporal raphe. Microvascular location is likely to be biologically relevant to many diseases, and so our spatial approach may be applicable to a diverse range of pathological features in the retina and other organs.

Item Type: Article
Uncontrolled Keywords: Science & Technology; Multidisciplinary Sciences; Science & Technology - Other Topics; COHERENCE TOMOGRAPHY ANGIOGRAPHY; CARDIAC IMAGING DATA; FLUORESCEIN ANGIOGRAMS; VEIN OCCLUSION; QUANTIFICATION; RETINOPATHY
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Computer Science
Applied Mathematics
Publisher: Nature Research (part of Springer Nature)
Related URLs:
Date Deposited: 17 Jun 2019 09:24
Last Modified: 17 Jun 2019 09:30
DOI or Identification number: 10.1038/s41598-017-16620-x
URI: http://researchonline.ljmu.ac.uk/id/eprint/10899

Actions (login required)

View Item View Item