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Title: | A deep learning model to detect the brain tumor based on magnetic resonance images |
Authors: | Rosnelly, Rika |
Keywords: | brain tumor detection, deep learning, inception v3, multi-layer perceptron |
Issue Date: | 28-Jul-2022 |
Publisher: | INFOTEL |
Abstract: | 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 that 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% and 56% accuracy, respectively. This research shows that the proposed model successfully predicts brain tumors and improves performance. |
Description: | Deep learning is a more robust and efficient than machine learning in many disciplines, especially medical image segmentation [1], [2]. Deep learning has been used in the medical industry to uncover new information and methods for detecting tumors and malignancies, including cervical cancer [3], breast cancer [4], liver tumors [5], lung tumors [6], and brain tumors [7]. One of the most dreaded illnesses in modern medicine is a brain tumor. Brain tumors are fibrous tissues that develop uncontrolled from abnormal brain tissue growth [8]. In the United States, an estimated 25,050 persons, including 10,880 women and 14,170 men, have been diagnosed with brain tumors according to a 2022 study by the American Society of Clinical Oncology (ASCO) [9]. |
URI: | http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5563 |
ISSN: | 2460-097 |
Appears in Collections: | A Paper |
Files in This Item:
File | Description | Size | Format | |
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46. A deep learning model to detect the brain tumor based onmagnetic resonance images.pdf | 798.71 kB | Adobe PDF | View/Open |
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