Naslov
CNN-based Method for Lung Cancer Detection in Whole Slide Histopathology Images

Autori
Šarić, Matko ; Russo, Mladen ; Stella, Maja ; Sikora, Marjan

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

Izvornik
Proceedings of 2019 4th International Conference on Smart and Sustainable Technologies (SpliTech) / - , 2019, 1-4

Skup
4th International Conference on Smart and Sustainable Technologies (SpliTech 2019)

Mjesto i datum
Split, Hrvatska; Bol, Hrvatska, 18.06.2019. - 21.06.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Covolutional neural networks ; lung cancer ; digital pathology

Sažetak
Early diagnosis of lung cancer is critical for improvement of patient survival. Histopathological assessment of tissue is standard procedure needed for early diagnosis. Tissue analysis is usually performed by pathologist review, but this procedure is time-consuming and error-prone. Automated detection of cancer regions would significantly speed up the whole process and help the pathologist. In this paper we propose fully automatic method for lung cancer detection in whole slide images of lung tissue samples. Classification is performed on image patch level using convolutional neural network (CNN). Two CNN architectures (VGG and ResNet) are trained and their performance are compared. Obtained results show that CNN based approach has potential to help pathologists in lung cancer diagnosis.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA