Pregled bibliografske jedinice broj: 983233
A Review of Image Processing and Deep Learning Based Methods for Automated Analysis of Digital Retinal Fundus Images
A Review of Image Processing and Deep Learning Based Methods for Automated Analysis of Digital Retinal Fundus Images // 2018 3rd International Conference on Smart and Sustainable Technologies (SpliTech)
Split, 2018. str. 1-6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
A Review of Image Processing and Deep Learning Based Methods for Automated Analysis of Digital Retinal Fundus Images
Autori
Braović, Maja ; Božić-Štulić, Dunja ; Stipaničev, Darko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2018 3rd International Conference on Smart and Sustainable Technologies (SpliTech)
/ - Split, 2018, 1-6
Skup
3rd International Conference on Smart and Sustainable Technologies (SpliTech 2018)
Mjesto i datum
Split, Hrvatska, 26.06.2018. - 29.06.2018
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
No keywords are given in this paper.
Sažetak
Retinal fundus imaging is a medical procedure used by medical professionals in the discovery and tracking of various retinal abnormalities. Sometimes the analysis of retinal fundus images can be slow and difficult when performed by medical staff, and in response to this many automated, image-processing based methods for the analysis of these images exist. In recent years, deep learning methods have become increasingly popular in machine learning applications, so it is no surprise that they are also being used in the image processing based analysis of retinal fundus images. In this paper we discuss recently proposed methods that use deep learning techniques in the image processing based analysis of digital retinal fundus images. Special attention is given to the analysis of retinal fundus image datasets and various techniques employed to the images from these datasets in order to make them suitable for deep learning based applications.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split