BRAIN TUMOR DETECTION USING DEEP LEARNING

BRAIN TUMOR DETECTION USING DEEP LEARNING

PRIYANKA SULADI1,  Mr.SIDDESH KT2, Mr.KOTRU SWAMY SM3

[1] Student Department Of MCA, BIET, Davangere

[2] Assistant Professor, Department Of MCA, BIET, Davangere

[3] Assistant Professor, Department Of MCA, BIET, Davangere

ABSTRACT

An illness known as a brain tumor is brought on by the expansion of aberrant brain cells. Brain tumors fall into two primary categories: benign brain tumors, which are non-cancerous, and malignant brain tumors, which are cancerous. Given the rarity and variety of brain tumors, it is challenging to forecast the survival rate of a patient who is tumor prone. According to UK cancer study, 15 out of every 100 patients with brain cancer will be able to live for ten years or longer following their diagnosis. The kind of brain tumor, the degree of cellular abnormality, the location of the tumor inside the brain, and other variables all affect the course of treatment. Deep learning models are used to diagnose problems as artificial intelligence advances.Images from magnetic resonance imaging are utilized to train deep learning models for brain tumor diagnosis. An example of a scanning technique is magnetic resonance imaging (MRI), which creates detailed images of the inside body by combining radio waves and strong magneticfields. Convolutional neural network (CNN) model which is constructed from scratch, are example of deep learning model used in this research project that are used to identify tumor regions in scanned brain pictures. 253 patients' brain MRI pictures were taken into consideration; 155 of these images showed tumors, and the remaining 98 did not.