Retinal vascular analysis in a fully automated method for the segmentation of DRT edemas using OCT images

被引:2
作者
de Moura, Joaquim [1 ,2 ]
Novo, Jorge [1 ,2 ]
Charlon, Pablo [3 ]
Isabel Fernandez, Maria [4 ,5 ,6 ]
Ortega, Marcos [1 ,2 ]
机构
[1] Univ A Coruna, Fac Informat, Dept Comp, La Coruna, Spain
[2] Univ A Coruna, CITIC Res Ctr Informat & Commun Technol, La Coruna, Spain
[3] Inst Oftalmol Victoria de Rojas, La Coruna, Spain
[4] Inst Oftalmol Gomez Ulla, Santiago De Compostela, Spain
[5] Univ Santiago, Dept Ophthalmol, Complejo Hosp, Santiago De Compostela, Spain
[6] Univ Santiago Compostela, Santiago De Compostela, Spain
来源
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019) | 2019年 / 159卷
关键词
Computer-aided diagnosis; optical coherence tomography; diabetic macular edema; retinal vascular structure; OPTICAL COHERENCE TOMOGRAPHY; DIABETIC MACULAR EDEMA; FLUID; IDENTIFICATION;
D O I
10.1016/j.procs.2019.09.215
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Optical Coherence Tomography (OCT) is a well-established medical imaging technique that allows a complete analysis and evaluation of the main retinal structures and their histopathology properties. Diabetic Macular Edema (DME) implies the accumulation of intraretinal fluid within the macular region. Diffuse Retinal Thickening (DRT) edemas are considered a relevant case of DME disease, where the pathological regions are characterized by a "sponge-like" appearance and a reduced intraretinal reflectivity, being visible in OCT images. Additionally, the presence of other structures may alter the OCT image characteristics, confusing the pathological identification process. This is the case of the retinal vessels over all the eye fundus, whose presence produce shadow projections over the retinal layers that may hide the "sponge-like" appearance of the DRT edemas. Thus, in this paper, we present a proposal for the automatic extraction of DRT edemas, also using as reference the information provided by the automatic identifications of the retinal vessels in the OCT images. To do that, firstly, the system delimits three retinal regions of interest. These retinal regions facilitate the posterior identification of the vessel structures and the segmentation of the DRT regions. For the identification of the vessels structures, the method combined the localization of the upper bright vascular profiles with the presence of their corresponding lower dark vascular shadows. Finally, a learning strategy is implemented for the segmentation of the DRT edemas. Satisfactory results were obtained, reaching values of 0.8346 and 0.9051 of Jaccard index and Dice coefficient, respectively, for the extraction of the existing DRT edemas. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码:600 / 609
页数:10
相关论文
共 20 条
[1]  
Bi J., 2003, Journal of Machine Learning Research, V3, P1229, DOI 10.1162/153244303322753643
[2]   Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography [J].
de Moura, Joaquim ;
Novo, Jorge ;
Rouco, Jose ;
Penedo, Manuel G. ;
Ortega, Marcos .
ARTIFICIAL INTELLIGENCE IN MEDICINE, AIME 2017, 2017, 10259 :305-315
[3]   Automatic Detection of Blood Vessels in Retinal OCT Images [J].
de Moura, Joaquim ;
Novo, Jorge ;
Rouco, Jose ;
Penedo, M. G. ;
Ortega, Marcos .
BIOMEDICAL APPLICATIONS BASED ON NATURAL AND ARTIFICIAL COMPUTING, PT II, 2017, 10338 :3-10
[4]   Computer-aided diagnosis in medical imaging: Historical review, current status and future potential [J].
Doi, Kunio .
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2007, 31 (4-5) :198-211
[5]  
Esmaeili Mahdad, 2016, J Med Signals Sens, V6, P166
[6]   Optical coherence tomography: An emerging technology for biomedical imaging and optical biopsy [J].
Fujimoto, JG ;
Pitris, C ;
Boppart, SA ;
Brezinski, ME .
NEOPLASIA, 2000, 2 (1-2) :9-25
[7]   Robust segmentation of retinal layers in optical coherence tomography images based on a multistage active contour model [J].
Gonzalez-Lopez, A. ;
de Moura, J. ;
Novo, J. ;
Ortega, M. ;
Penedo, M. G. .
HELIYON, 2019, 5 (02)
[8]  
Gunn S. R., 1998, ISIS TECH REP, V14, P5
[9]   Feature selection: Evaluation, application, and small sample performance [J].
Jain, A ;
Zongker, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (02) :153-158
[10]  
Li XQ, 2017, BIOMED RES-TOKYO, V28, P9423