1.

Record Nr.

UNINA9910350228303321

Titolo

Retinal Optical Coherence Tomography Image Analysis / / edited by Xinjian Chen, Fei Shi, Haoyu Chen

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019

ISBN

981-13-1825-5

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (XI, 385 p. 189 illus., 156 illus. in color.)

Collana

Biological and Medical Physics, Biomedical Engineering, , 1618-7210

Disciplina

621.36

Soggetti

Lasers

Photonics

Medical physics

Radiation

Biomedical engineering

Optical data processing

Radiology

Ophthalmology

Optics, Lasers, Photonics, Optical Devices

Medical and Radiation Physics

Biomedical Engineering and Bioengineering

Computer Imaging, Vision, Pattern Recognition and Graphics

Imaging / Radiology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Clinical applications of retinal optical coherence tomography -- Fundamentals of optical coherence tomography -- Speckle noise reduction and enhancement for OCT images -- Reconstruction of retinal OCT images with sparse representation -- Segmentation of OCT scans using probabilistic graphical models -- Diagnostic capability of optical coherence tomography based quantitative analysis for various eye diseases and additional factors affecting morphological measurements -- Quantitative analysis of retinal layers' optical intensities based on optical coherence tomography -- Segmentation of optic disc and cup-to-disc ratio quantification based on OCT scans --



Choroidal OCT analytics -- Layer segmentation and analysis for retina with diseases -- Segmentation and visualization of drusen and geographic atrophy in SD-OCT images -- Segmentation of symptomatic exudate-associated derangements in 3D OCT images -- Modeling and prediction of chroidal neovascularization growth based on longitudinal OCT scans.

Sommario/riassunto

This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging.