Naslov
URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES

Autori
Lorencin, Ivan ; Baressi Šegota, Sandi ; Anđelić, Nikola ; Mrzljak, Vedran ; Smolić, Klara ; Španjol, Josip ; Car, Zlatan

Izvornik
World of health (2623-5773) 4 (2022); 64-69

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
AI ; CNN ; Urinary Bladder Cancer

Sažetak
Bladder cancer is one of the most common malignancies in men in Croatia. It is characterized by a high recurrence rate and high metastatic potential. For this reason, accurate and timely diagnosis is needed in order to treat bladder cancer as successfully as possible. Cystoscopy as a diagnostic method shows poorer accuracy of Carcinoma in situ (CIS) diagnosis, where every fourth CIS remains undiagnosed. For this reason, the artificial intelligence-based approach is proposed. The standard approach to image classification is utilization of convolutional neural networks (CNN). Literature overview shows a possibility of using pre-defined CNN models, such as VGG-16. VGG- 16, in this case, needs to be customized in order to adapt it to four-class classification problem. By using a customized VGG-16 model, high classification performances are achieved. When AdaGrad and AdaMax solvers are used, AUC micro values up to 0.98 are achieved.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti, Temeljne medicinske znanosti, Kliničke medicinske znanosti

POVEZANOST RADA