Next Article in Journal
A Distance Increment Smoothing Method and Its Application on the Detection of NLOS in the Cooperative Positioning
Next Article in Special Issue
Decision Trees for Glaucoma Screening Based on the Asymmetry of the Retinal Nerve Fiber Layer in Optical Coherence Tomography
Previous Article in Journal
Integration and Application of Multimodal Measurement Techniques: Relevance of Photogrammetry to Orthodontics
Previous Article in Special Issue
Bluetooth Low Energy Beacon Sensors to Document Handheld Magnifier Use at Home by People with Low Vision
 
 
Article

Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging

1
Departamento de Ciencias Politécnicas, Campus de los Jerónimos, Universidad Católica de Murcia UCAM, 30107 Murcia, Spain
2
Departamento de Tecnologías de la Información y Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain
3
Servicio de Oftalmología, Hospital General Universitario Reina Sofía, 30003 Murcia, Spain
4
Instituto de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Boris I. Gramatikov
Sensors 2021, 21(23), 8027; https://doi.org/10.3390/s21238027
Received: 29 September 2021 / Revised: 17 November 2021 / Accepted: 25 November 2021 / Published: 1 December 2021
(This article belongs to the Special Issue Sensors in Vision Research and Ophthalmic Instrumentation)
Glaucoma is a neurodegenerative disease process that leads to progressive damage of the optic nerve to produce visual impairment and blindness. Spectral-domain OCT technology enables peripapillary circular scans of the retina and the measurement of the thickness of the retinal nerve fiber layer (RNFL) for the assessment of the disease status or progression in glaucoma patients. This paper describes a new approach to segment and measure the retinal nerve fiber layer in peripapillary OCT images. The proposed method consists of two stages. In the first one, morphological operators robustly detect the coarse location of the layer boundaries, despite the speckle noise and diverse artifacts in the OCT image. In the second stage, deformable models are initialized with the results of the previous stage to perform a fine segmentation of the boundaries, providing an accurate measurement of the entire RNFL. The results of the RNFL segmentation were qualitatively assessed by ophthalmologists, and the measurements of the thickness of the RNFL were quantitatively compared with those provided by the OCT inbuilt software as well as the state-of-the-art methods. View Full-Text
Keywords: optical coherence tomography (OCT); peripapillary OCT; automatic layer segmentation; retinal imaging analysis; mathematical morphology; active contours; glaucoma optical coherence tomography (OCT); peripapillary OCT; automatic layer segmentation; retinal imaging analysis; mathematical morphology; active contours; glaucoma
Show Figures

Figure 1

MDPI and ACS Style

Berenguer-Vidal, R.; Verdú-Monedero, R.; Morales-Sánchez, J.; Sellés-Navarro, I.; del Amor, R.; García, G.; Naranjo, V. Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging. Sensors 2021, 21, 8027. https://doi.org/10.3390/s21238027

AMA Style

Berenguer-Vidal R, Verdú-Monedero R, Morales-Sánchez J, Sellés-Navarro I, del Amor R, García G, Naranjo V. Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging. Sensors. 2021; 21(23):8027. https://doi.org/10.3390/s21238027

Chicago/Turabian Style

Berenguer-Vidal, Rafael, Rafael Verdú-Monedero, Juan Morales-Sánchez, Inmaculada Sellés-Navarro, Rocío del Amor, Gabriel García, and Valery Naranjo. 2021. "Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging" Sensors 21, no. 23: 8027. https://doi.org/10.3390/s21238027

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop