brain tumor detection system using VGG16 architecture
Tumor can define as the abnormal or extraordinary growth of the human's tissues. Therefor brain tumor can be simply described as the abnormal or extraordinary growth of cell within the brain. Different type of the brain tumors are Exists. Some brain tumors are noncancerous and a few brain tumors are cancerous. Further some brain tumors can begin in the brain or some cancer can begin in other parts of body. Magnetic resonance imaging (MRI) plays an important role in brain tumor for analysis, diagnosis, and treatment planning. Magnetic resonance imaging (MRI) is an advanced medical imaging technique used to produce high quality images of the parts contained in the human body MRI images is often used when treating brain tumors. It is very helpful to doctor for determining the previous steps of brain tumor. The detections of brain tumor using MRI images is a challenging task because of the complex structure of the brain. This project aims to identify brain tumors using CCN's VGG 16 architecture
It also includes the Convolution Neural Network architecture is VGG 16 algorithm which identifies whether the image is affected by the tumor or not. This method of extracting features from images is currently gaining popularity. The brain tumor MRI images used for this model were used as a secondary data collection method and have been used for research in the past.
dataset link - https://www.kaggle.com/navoneel/brain-mri-images-for-brain-tumor-detection