Affiliations:
Department of Computer Science and Technology, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
Correspondence:
[*]
Corresponding author. Jinniu Bai, Department of Computer Science and Technology, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou 014040, China. E-mail: [email protected].
Abstract: Brain cancer is one of the most deadly forms of cancer today, and its timely and accurate diagnosis can significantly impact the patient’s quality of life. A computerized tomography scan (CT) and magnetic resonance imaging (MRI) of the brain is required to diagnose this condition. In the past, several methods have been proposed as a means of diagnosing brain tumors through the use of medical images. However, due to the similarity between tumor tissue and other brain tissues, these methods have not proven to be accurate. A novel method for diagnosing brain tumors using MRI and CT scan images is presented in this paper. An architecture based on deep learning is used to extract the distinguishing characteristics of brain tissue from tumors. The use of fusion images allows for more accurate detection of tumor types. In comparison with other approaches, the proposed method has demonstrated superior results.
