Naslov
Histopathological H&E-Stained Image Analysis Based on AI

Autori
Musulin, Jelena ; Štifanić, Daniel ; Zulijani, Ana ; Baressi Šegota, Sandi ; Anđelić, Nikola ; Lorencin, Ivan ; Glučina, Matko ; Car, Zlatan

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prošireni sažetak, znanstveni

Izvornik
First Serbian Conference on Applied Artificial Intelligence / - Kragujevac, 2022

Skup
1st Serbian International Conference on Applied Artificial Intelligence (SICAAI)

Mjesto i datum
Kragujevac, Srbija, 19.05.2022. - 20.05.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
artificial intelligence, convolutional neural network, histopathological analysis, oral squamous cell carcinoma

Sažetak
Over the past decade, improvements in image analysis methods and substantial advancements in processing power have allowed the development of powerful computer-aided analytical approaches to medical data. Tissue histology slides can now be scanned and preserved in digital form, thanking to the recent introduction of the entire slide digital scanners. In such form, they can serve as input data for Artificial Intelligence (AI) algorithms that can speed up standard procedures for histology analysis with high accuracy and precision. The aim of this research was to create an automated system based on AI for histopathological image analysis. The first step was to normalize H&E-stain images, and then use them as an input to the convolutional neural network. The best results are achieved using ResNet50 with highest AUC value of 0.98 (±σ=0.02). Such an approach proved to be successful in analyzing histopathological images.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti, Interdisciplinarne tehničke znanosti, Biotehnologija u biomedicini (prirodno područje, biomedicina i zdravstvo, biotehničko područje)

POVEZANOST RADA