**Author details**

diseases that affect the retinal microcirculation, such as hypertension, diabetes or arterio-

CAD systems have become increasingly important in the assessment of outcomes in the daily clinical practice, mainly in the field of medical imaging-based diagnosis. These systems help the clinical experts in the analysis and interpretation of several modalities of medical images,

OCT is a noninvasive imaging modality capable of producing high-speed three-dimensional cross-sectional imaging of biological tissues with micron-level resolution. This medical image modality enables the precise evaluation of the retinal structure in real time, permitting the detection of alterations in the retinal microcirculation. The OCT devices provide two types of OCT images: the NIR retinography image and the OCT histological sections. These images

In this chapter, we analyzed the characteristics of the OCT scans and their suitability for the vascular analysis. Additionally, we presented two different and independent approaches for the automatic identification and extraction of the retinal vascular structure to highlight the potential of these computational approaches in the field. The first approach uses the information provided by the NIR retinography image in combination with the histological sections. The second approach uses only the information provided by the OCT histological sections for the characterization of the vessel profiles. Then, both computational approaches perform the corresponding graphical two-dimensional or three-dimensional visual representation of the

These fully automatic systems allow a more accurate and reliable visualization of the complex vascular structure of the retina, and consequently, make an improvement in the visual inspection and analyses of the retinal vessel tree. In addition, the vessel representation permits a more precise analysis of the retinal microcirculation, making the diagnosis of various retinal

This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund-ERDF) and the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016-2019, Ref. ED431G/01; and

are frequently acquired simultaneously by the same capture device.

retinal vessel tree using the extracted information.

and systemic pathologies easier for doctors.

Grupos de Referencia Competitiva, Ref. ED431C 2016-047.

The authors declare that they have no conflict of interest.

**Acknowledgements**

**Conflict of interest**

sclerosis, among others.

36 OCT - Applications in Ophthalmology

facilitating and simplifying their work.

Joaquim de Moura1,2, Jorge Novo1,2\*, José Rouco1,2, Noelia Barreira1,2, Manuel Penedo1,2 and Marcos Ortega1,2

\*Address all correspondence to: jnovo@udc.es

1 Department of Computing, University of A Coruña, A Coruña, Spain

2 Research Center of Information and Communication Technologies (CITIC), University of A Coruña, A Coruña, Spain
