Detection of brain tumours using deep learning model

• Main Authors: Jayapradha, J., Sourav, Subham, Singh, Devdeep, Devi, M. Uma
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial neural networks; Brain; Brain cancer; Cancer; Deep learning; Image processing; Machine learning; Medical imaging; Neural networks; Physicians; Tumors
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0217153

Tumours are currently the most common cancer cause. Many patients are at risk as a result of cancer. To detect tumours like brain tumours, the medical sector needs a quick, automated, effective, and trustworthy technique. A crucial part of treatment is detection. Doctors keep a patient out of danger if accurate tumour identification is possible. In this application, many image processing methods are applied. Doctors treat many tumour patients properly and save their lives using this application. Currently, medical professionals manually inspect the patient’s Magnetic imaging scans of the brain to identify the position and magnitude of the brain neoplasm. This process is time-consuming and results in imprecise detection of the neoplasm. To identify brain tumours, we can apply a Deep Learning framework integrating Convolutional Neural Network (CNN), also called Neural Network, with Visual Geometry Group (VGG) 16 Transfer learning. The advantage of the model is to anticipate the existence of a tumour in an image by returning a positive result if present and a negative effect if not.