Deep convolutional networks for OCT image classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU131972" target="_blank" >RIV/00216305:26220/19:PU131972 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Deep convolutional networks for OCT image classification
Original language description
In this work, OCT (optical coherence tomography) images are classified according to the present pathology into four distinct categories. Three different neural network models are used to classify images, each model is recent and we are achieving exceptional results on the testing dataset, which was unknown to the network during the training. Accuracy on the testing set is higher than 98% and only a few of images are classified into the wrong category. This makes our approach perspective for future automatic use. To further improve results, all three models are using transfer learning.
Czech name
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Czech description
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Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 25th Conference STUDENT EEICT 2019
ISBN
978-80-214-5735-5
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
437-442
Publisher name
Vysoké učení technické vBrně, Fakulta elektrotechniky a komunikačních technologií
Place of publication
Brno
Event location
Brno
Event date
Apr 26, 2018
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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