Evidence map›Paper›PMID 31827591›Full record

ArticleComputational and mathematical methods in medicine2019

Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior.

Wei Zhou, Yugen Yi, Yuan Gao, Jiangyan Dai

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Wei ZhouCollege of Computer Science, Shenyang Aerospace University, Shenyang, Liaoning, China.ORCID https://orcid.org/0000-0002-5931-3197
Yugen YiSchool of Software, Jiangxi Normal University, Nanchang, Jiangxi, China.ORCID https://orcid.org/0000-0002-2726-9873
Yuan GaoCollege of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China.ORCID https://orcid.org/0000-0002-3376-8433
Jiangyan DaiSchool of Computer Engineering, Weifang University, Weifang, China.ORCID https://orcid.org/0000-0003-4893-3750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate optic disc and optic cup segmentation plays an important role for diagnosing glaucoma. However, most existing segmentation approaches suffer from the following limitations. On the one hand, image devices or illumination variations always lead to intensity inhomogeneity in the fundus image. On the other hand, the spatial prior knowledge of optic disc and optic cup, e.g., the optic cup is always contained inside the optic disc region, is ignored. Therefore, the effectiveness of segmentation approaches is greatly reduced. Different from most previous approaches, we present a novel locally statistical active contour model with the structure prior (LSACM-SP) approach to jointly and robustly segment the optic disc and optic cup structures. First, some preprocessing techniques are used to automatically extract initial contour of object. Then, we introduce the locally statistical active contour model (LSACM) to optic disc and optic cup segmentation in the presence of intensity inhomogeneity. Finally, taking the specific morphology of optic disc and optic cup into consideration, a novel structure prior is proposed to guide the model to generate accurate segmentation results. Experimental results demonstrate the advantage and superiority of our approach on two publicly available databases, i.e., DRISHTI-GS and RIM-ONE r2, by comparing with some well-known algorithms.

Indexed as

AlgorithmsCluster AnalysisDiagnosis, Computer-AssistedFalse Positive ReactionsFundus OculiGlaucomaHumansImage Processing, Computer-AssistedModels, StatisticalNormal DistributionOphthalmologyOptic DiskPattern Recognition, AutomatedReproducibility of ResultsRetinaROC Curve

Identifiers

PMID31827591
PMCPMC6886352

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.