Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images
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Joint Diabetic Macular Edema Segmentation and Characterization in OCT ImagesAutor(es)
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2020-06-19Cita bibliográfica
de Moura, J., Samagaio, G., Novo, J. et al. Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images. J Digit Imaging 33, 1335–1351 (2020). https://doi.org/10.1007/s10278-020-00360-y
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https://doi.org/10.1007/s10278-020-00360-y
Resumo
[Abstract]: The automatic identification and segmentation of edemas associated with diabetic macular edema (DME) constitutes a crucial ophthalmological issue as they provide useful information for the evaluation of the disease severity. According to clinical knowledge, the DME disorder can be categorized into three main pathological types: serous retinal detachment (SRD), cystoid macular edema (CME), and diffuse retinal thickening (DRT). The implementation of computational systems for their automatic extraction and characterization may help the clinicians in their daily clinical practice, adjusting the diagnosis and therapies and consequently the life quality of the patients. In this context, this paper proposes a fully automatic system for the identification, segmentation and characterization of the three ME types using optical coherence tomography (OCT) images. In the case of SRD and CME edemas, different approaches were implemented adapting graph cuts and active contours for their identification and precise delimitation. In the case of the DRT edemas, given their fuzzy regional appearance that requires a complex extraction process, an exhaustive analysis using a learning strategy was designed, exploiting intensity, texture, and clinical-based information. The different steps of this methodology were validated with a heterogeneous set of 262 OCT images, using the manual labeling provided by an expert clinician. In general terms, the system provided satisfactory results, reaching Dice coefficient scores of 0.8768, 0.7475, and 0.8913 for the segmentation of SRD, CME, and DRT edemas, respectively.
Palabras chave
Optical coherence tomography
Diabetic macular edema
Fluid segmentation
Computer-aided diagnosis
Retinal imaging
Diabetic macular edema
Fluid segmentation
Computer-aided diagnosis
Retinal imaging
Descrición
This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10278-020-00360-y
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ISSN
0897-1889