Dataset Information

Development of a semi-automatic segmentation method for retinal OCT images tested in patients with diabetic macular edema.

ABSTRACT: PURPOSE: To develop EdgeSelect, a semi-automatic method for the segmentation of retinal layers in spectral domain optical coherence tomography images, and to compare the segmentation results with a manual method. METHODS: SD-OCT (Heidelberg Spectralis) scans of 28 eyes (24 patients with diabetic macular edema and 4 normal subjects) were imported into a customized MATLAB application, and were manually segmented by three graders at the layers corresponding to the inner limiting membrane (ILM), the inner segment/ellipsoid interface (ISe), the retinal/retinal pigment epithelium interface (RPE), and the Bruch's membrane (BM). The scans were then segmented independently by the same graders using EdgeSelect, a semi-automated method allowing the graders to guide/correct the layer segmentation interactively. The inter-grader reproducibility and agreement in locating the layer positions between the manual and EdgeSelect methods were assessed and compared using the Wilcoxon signed rank test. RESULTS: The inter-grader reproducibility using the EdgeSelect method for retinal layers varied from 0.15 to 1.21 µm, smaller than those using the manual method (3.36-6.43 µm). The Wilcoxon test indicated the EdgeSelect method had significantly better reproducibility than the manual method. The agreement between the manual and EdgeSelect methods in locating retinal layers ranged from 0.08 to 1.32 µm. There were small differences between the two methods in locating the ILM (p = 0.012) and BM layers (p<0.001), but these were statistically indistinguishable in locating the ISe (p = 0.896) and RPE layers (p = 0.771). CONCLUSIONS: The EdgeSelect method resulted in better reproducibility and good agreement with a manual method in a set of eyes of normal subjects and with retinal disease, suggesting that this approach is feasible for OCT image analysis in clinical trials.

SUBMITTER: Huang Y

PROVIDER: S-EPMC3873283 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Development of a semi-automatic segmentation method for retinal OCT images tested in patients with diabetic macular edema.

Huang Yijun Y Danis Ronald P RP Pak Jeong W JW Luo Shiyu S White James J Zhang Xian X Narkar Ashwini A Domalpally Amitha A

PloS one 20131226 12

<h4>Purpose</h4>To develop EdgeSelect, a semi-automatic method for the segmentation of retinal layers in spectral domain optical coherence tomography images, and to compare the segmentation results with a manual method.<h4>Methods</h4>SD-OCT (Heidelberg Spectralis) scans of 28 eyes (24 patients with diabetic macular edema and 4 normal subjects) were imported into a customized MATLAB application, and were manually segmented by three graders at the layers corresponding to the inner limiting membra ...[more]

PMID: 24386127

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Project description:Given the capacity of Optical Coherence Tomography (OCT) imaging to display structural changes in a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more than ever before. In this paper, we wish to address this need by designing a semi-automatic software program for applying reliable segmentation of 8 different macular layers as well as outlining retinal pathologies such as diabetic macular edema. The software accommodates a novel graph-based semi-automatic method, called "Livelayer" which is designed for straightforward segmentation of retinal layers and fluids. This method is chiefly based on Dijkstra's Shortest Path First (SPF) algorithm and the Live-wire function together with some preprocessing operations on the to-be-segmented images. The software is indeed suitable for obtaining detailed segmentation of layers, exact localization of clear or unclear fluid objects and the ground truth, demanding far less endeavor in comparison to a common manual segmentation method. It is also valuable as a tool for calculating the irregularity index in deformed OCT images. The amount of time (seconds) that Livelayer required for segmentation of Inner Limiting Membrane, Inner Plexiform Layer-Inner Nuclear Layer, Outer Plexiform Layer-Outer Nuclear Layer was much less than that for the manual segmentation, 5 s for the ILM (minimum) and 15.57 s for the OPL-ONL (maximum). The unsigned errors (pixels) between the semi-automatically labeled and gold standard data was on average 2.7, 1.9, 2.1 for ILM, IPL-INL, OPL-ONL, respectively. The Bland-Altman plots indicated perfect concordance between the Livelayer and the manual algorithm and that they could be used interchangeably. The repeatability error was around one pixel for the OPL-ONL and < 1 for the other two. The unsigned errors between the Livelayer and the manual algorithm was 1.33 for ILM and 1.53 for Nerve Fiber Layer-Ganglion Cell Layer in peripapillary B-Scans. The Dice scores for comparing the two algorithms and for obtaining the repeatability on segmentation of fluid objects were at acceptable levels.

Project description:Importance:In diabetic macular edema (DME), identification of baseline markers on spectral-domain optical coherence tomography (SD-OCT) and their association with severity of diabetic retinopathy (DR) might aid in disease management and the design of future trials. Objective:To examine associations between DR severity, retinal morphology on SD-OCT, and visual acuity in participants with DME. Design, Setting, and Participants:This cross-sectional observational case series was conducted at a single tertiary care referral center. Demographics, visual acuity, SD-OCT, and color fundus photographs of 80 individuals with DME (102 eyes) seen between December 28, 2013, and April 30, 2014, were analyzed between May 1 and July 31, 2016. Main Outcomes and Measures:Features captured on SD-OCT and thickness metrics. On SD-OCT we graded type and shape of DME, shape and presence of septae within the intraretinal cystoid abnormalities, presence of hyperreflective dots and foci, integrity of the external limiting membrane and ellipsoid zone, presence and extent of disorganization of the inner retinal layers (DRIL), and the status of the vitreomacular interface and epiretinal membrane. We measured retinal thickness at the fovea and at the site of maximum pathology, choroidal thickness at the fovea, and 1000 ?m temporal and nasal to the fovea. Color photographs were graded to derive a DR severity stage. Results:The mean (SD) age was 63 (11) years, and 30 participants (37.5%) were women. The odds of having DRIL were greater in eyes with disrupted external limiting membrane (odds ratio [OR], 4.4; 95% CI, 1.6-12.0; P?=?.003), disrupted ellipsoid zone (OR, 2.7; 95% CI, 1.0-7.2; P?=?.03), presence of epiretinal membrane (OR, 2.8; 95% CI, 1.0-7.4; P?=?.03), and increase in retinal thickness at the fovea (OR, 1.6; 95% CI, 1.1-2.2; P?<?.001). Occurrence of DRIL was more likely in eyes with proliferative DR (OR, 7.3; 95% CI, 1.7-31.4; P?=?.007). Mean visual acuity decreased by approximately 4.7 letters for each 100-?m increase in the average global DRIL (95% CI, -7.9 to 1.4; P?=?.006). Conclusions and Relevance:An association was found between DRIL and disruption of the outer retina and increasing DR severity. Further longitudinal studies seem warranted to determine whether DRIL is a clinically relevant noninvasive morphological marker in eyes with DME.

Dataset Information

Development of a semi-automatic segmentation method for retinal OCT images tested in patients with diabetic macular edema.

Publications

Development of a semi-automatic segmentation method for retinal OCT images tested in patients with diabetic macular edema.

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