Naslov
Retinal Vessel Segmentation Using Deep Neural Networks

Autori
Melinščak, Martina ; Prentašić, Pavle ; Lončarić, Sven

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
VISAPP 2015 (10th International Conference on Computer Vision Theory and Applications), Proceedings, Vol.1 / José Braz, Sebastiano Battiato and Francisco Imai - , 2015, 577-582

ISBN
978-989-758-089-5

Skup
10th International Conference on Computer Vision Theory and Applications (VISAPP 2015)

Mjesto i datum
Berlin, Njemačka, 11.03.2015. - 14.03.2015

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Blood vessel segmentation ; retinal imaging ; deep neural networks ; GPU

Sažetak
Automatic segmentation of blood vessels in fundus images is of great importance as eye diseases as well as some systemic diseases cause observable pathologic modifications. It is a binary classification problem: for each pixel we consider two possible classes (vessel or non-vessel). We use a GPU implementation of deep max-pooling convolutional neural networks to segment blood vessels. We test our method on publicly-available DRIVE dataset and our results demonstrate the high effectiveness of the deep learning approach. Our method achieves an average accuracy and AUC of 0.9466 and 0.9749, respectively.

Izvorni jezik
Engleski

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