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A mobile computer aided system for optic nerve head detection.

Abstract：

BACKGROUND AND OBJECTIVE:The detection of optic nerve head (ONH) in retinal fundus images plays a key role in identifying Diabetic Retinopathy (DR) as well as other abnormal conditions in eye examinations. This paper presents a method and its associated software towards the development of an Android smartphone app based on a previously developed ONH detection algorithm. The development of this app and the use of the d-Eye lens which can be snapped onto a smartphone provide a mobile and cost-effective computer-aided diagnosis (CAD) system in ophthalmology. In particular, this CAD system would allow eye examination to be conducted in remote locations with limited access to clinical facilities. METHODS:A pre-processing step is first carried out to enable the ONH detection on the smartphone platform. Then, the optimization steps taken to run the algorithm in a computationally and memory efficient manner on the smartphone platform is discussed. RESULTS:The smartphone code of the ONH detection algorithm was applied to the STARE and DRIVE databases resulting in about 96% and 100% detection rates, respectively, with an average execution time of about 2 s and 1.3 s. In addition, two other databases captured by the d-Eye and iExaminer snap-on lenses for smartphones were considered resulting in about 93% and 91% detection rates, respectively, with an average execution time of about 2.7 s and 2.2 s, respectively.

journal_name

Comput Methods Programs Biomed

journal_title

Computer methods and programs in biomedicine

authors

Elloumi Y,Akil M,Kehtarnavaz N

doi

10.1016/j.cmpb.2018.05.004

subject

Has Abstract

pub_date

2018-08-01 00:00:00

pages

139-148

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(17)31047-7

journal_volume

162

pub_type

杂志文章

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