KLASIFIKASI CITRA CT SCAN HATI UNTUK DETEKSI PENYAKIT TUMOR HATI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Andini, Yuli Kuswardani, Dwina Siregar, Riki Ruli A
Subject
Teknik Elektro
Datestamp
2023-06-07 02:27:33
Abstract :
Liver tumors can be caused by excessive cell growth in the liver organs. This study aims to
determine the classification of Liver CT Scan images in the detection of Liver Tumor
disease using the Convolutional Neural Network (CNN) method with the Inception
ResnetV2 architecture which is based on helping ordinary people or medical personnel
make a decision in diagnosing liver tumor disease early. The Convolutional Neural Network
(CNN) method with the Inception ResnetV2 architecture was chosen because this method
produces excellent performance in classifying 2-dimensional image data and the resulting
training model results have relatively low computation. The accuracy training results of the
Convolutional Neural Network (CNN) architecture that have been made show an accuracy
of 98% and the results of the application training validation show an accuracy of 92.5%.