Abstrak
Deep learning techniques have been widely used in everything from analyzing medical information to tools for making medical diagnoses. One of the most feared diseases in modern medicine is a brain tumor. MRI is a radiological method hat can be used to identify brain tumors. However, manual segmentation and analysis of MRI images is time-consuming and can only be performed by a professional neuroradiologist. Therefore automatic recognition is required. This study propose a deep learning method based on a hybrid multi-layer perceptron model with Inception-v3 to predict brain tumors using MRI images. The research was conducted by building the Inception-v3 and multilayer perceptron model, and comparing it with the proposed model. The results showed that the hybrid multilayer perceptron model with Inception-v3 achieved accuracy, recall, precision, and fi-score of 92%. While the Inception-v3 and multilayer perceptron models only obtained 66% and56% accuracy, respectively. This research shows that the proposed model successfully predicts brain tumors and improves performance.
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Kelvin Leonardi Kohsasih
Universitas Potensi Utama
Muhammad Dipo Agung Rizky
Universitas Potensi Utama
Rika Rosnelly
Universitas Potensi Utama
Willy Wira Widjaja
Tunghai University
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Citation:
K. Kohsasih, M. D. Agung Rizky, R. Rosnelly, and W. W. Widjaja, “A deep learning model to detect the brain tumor based on magnetic resonance images”, INFOTEL, vol. 14, no. 3, pp. 205-210, Aug. 2022.
Publication:
Vol 9 No 1 (2022): Jurnal INFOTEL
DOI:
10.20895/infotel.v14i3.793
Copyright:
Copyright (c) Jurnal Infotel