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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Nuthanakanti Bhaskar
CMR Technical Campus
Computer Science & IT

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An approach for liver cancer detection from histopathology images using hybrid pre-trained models Nuthanakanti Bhaskar; Jangala Sasi Kiran; Suma Satyanarayan; Gaddam Divya; Kotagiri Srujan Raju; Murali Kanthi; Raj Kumar Patra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.25588

Abstract

Histopathological image analysis (HIA) plays an essential role in detecting cancer cell development, but it is time-consuming, prone to inaccuracy, and dependent on pathologist competence. This paper proposes an automated HIA that uses deep learning to improve accuracy and efficiency in liver cancer cell growth. The model uses whole slide image (WSI) input, open computer vision (OpenCV) libraries for image preprocessing, ResNet50 for patch-level feature extraction, and multiple instances learning for image-level classification. The suggested approach accurately distinguishes liver histopathological pictures as cancerous or non-cancerous. Assisting in the early detection of liver cancer cell development with potential invasion or spread.
Co-Authors Gaddam Divya Jangala Sasi Kiran Kotagiri Srujan Raju Murali Kanthi Raj Kumar Patra Suma Satyanarayan