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All Journal Jurnal Akuntansi dan Pajak Jurnal Informatika IT JOURNAL RESEARCH AND DEVELOPMENT METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Kolaboratif Sains Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jutech: Jurnal Teknologi Informasi JURSIMA Jurnal Pengabdian Kepada Masyarakat Al-Amin
Rian Ardianto
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Journal : IT JOURNAL RESEARCH AND DEVELOPMENT

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CNN-based Classification of Bladder Tissue Lesions from Endoscopy Images Lutviana, Lutviana; Rian Ardianto; Purwono
IT Journal Research and Development Vol. 9 No. 2 (2025)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2025.17867

Abstract

Bladder cancer is one type of tumor that frequently occurs in the urinary system, and early diagnosis is essential to improve the prognosis and survival of patients. The study aims to develop a Convolutional Neural Network (CNN) model for bladder tissue lesion classification from endoscopic images. This study uses a dataset consisting of 1754 images, which are divided into four classes: High-Grade Cancer (HGC), Low-Grade Cancer (LGC), Non-Specific Tissue (NST), and Non-Tumorous Lesion (NTL). The proposed CNN model showed a validation accuracy of 96.29%, with high recall, precision, and F1-score in most classes. The results show that CNN-based automated methods can improve efficiency and accuracy in the early diagnosis of bladder cancer, reduce manual visual interpretation errors, and improve the quality of patient care. This study suggests increasing the training data, especially for the NTL class, and applying more complex model architecture to better results.
Co-Authors Aina Filhiam Annisa Risqi Sulistya Kusuma Wardhani Arif Setia Sandi A. Asti Herliana, Asti Dasril Aldo Deny Nugroho Triwibowo Dewi Lestari Dimas Febri Kuncoro Dini Silvi Purnia, Dini Silvi Girman Sihombing Hadi Jayusman Jessa Syah Putra Karyaningsih Karyaningsih Lutviana, Lutviana Moh Khoridatul Huda, Moh Khoridatul Muh. Jaelani Al Pansori Muhammad Jainul Amri Lubis Nurul Wahyuni Mahmud Purwono Ramadya Wahyu Dwinanto Rini Novianti Rosyid Ridlo Al-Hakim Sjahruddin, Herman Sonny Santosa Sony Kartika Wibisono Tb. Dedy Fuady Tia Rohliana Tuti Alawiyah Yazid Ilham Dia Uddin