Pregled bibliografske jedinice broj: 1033168
Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis
Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis // Artificial intelligence in medicine, 102 (2019), 1-16 doi:10.1016/j.artmed.2019.101746 (međunarodna recenzija, članak, znanstveni)
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Naslov
Using multi-layer perceptron with Laplacian edge
detector for bladder cancer diagnosis
Autori
Lorencin, Ivan ; Anđelić, Nikola ; Španjol, Josip ; Car, Zlatan
Izvornik
Artificial intelligence in medicine (0933-3657) 102
(2019);
1-16
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Artificial intelligence ; Image pre-processing ; Laplacian edge detector ; Multi-layer perceptron ; Urinary bladder cancer
Sažetak
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi- Layer Perceptron) alongside commonly used methods, such as Deep LearningConvolutional Neural Networks, for the urinary bladder cancer detection. The dataset used for this research consisted of 1997 images of bladder cancer and 986 images of non-cancer tissue. The results of the conducted research showed that using Multi-Layer Perceptron trained and tested with images pre-processed with Laplacianedge detector are achievingAUCvalue up to 0.99. When different image sizes are compared it can be seen that the best results are achieved if×5050and×100 100images were used.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti, Temeljne medicinske znanosti, Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Medicinski fakultet, Rijeka,
Tehnički fakultet, Rijeka,
Klinički bolnički centar Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE