| Autor: |
Indriani, Karlena, Puspitasari, Diah, Widiati, Wina, Yulianto, Eko, Pratiwi, Asta, Ramanda, Kresna |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 5/12/2023, Vol. 2714 Issue 1, p1-6, 6p |
| Abstrakt: |
Brain tumors are a group of tumors consisting of various elements with different elements. The incidence varies according to tumor type, sex, race and age. The classification of brain tumors is quite a challenging job in the field of medical image processing. The tumor classification model is important for assisting radiologists in detecting brain tumors. The brain tumor classification model using the Convolutional Neural Network has a high degree of accuracy. The proposed system has six feature extraction layers and two classification layers in three steps, Pre-processing that changes the image size, feature extraction and classification using Convolutional Neural Network (CNN) is proposed in this study. The application of feature extraction using Convolution Neural Network (CNN) can retrieve information from images and become a tool for classifying brain tumor image types into four classes, namely Glioma Tumors, Meningioma Tumors, Pituitary Tumors and Without Tumors which can produce better classification with accuracy amounted to 98.93%. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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