• Divya Tiwari
• Kantilal Vishwakarma
• Kunal Ruhela
• Vranda Khetan
• Sunil yadav

Brain Tumor is an abnormal intracranial growth caused by cells reproducing themselves in an uncontrolled manner. Most researches in the developed countries shows that main cause of death of people having Brain Tumor is incorrect detection of Brain Tumor. It is one of the most dangerous diseases and therefore it should be detected quickly and accurately. Generally, MRI or CT scan that is directed into the intracranial cavity produces the complete image of the Brain Tumor. Magnetic Resonance Imaging (MRI), a highly developed technique of medical imaging is used to visualize internal structure of human body without any surgery. For the accurate detection of Brain Tumor segmentation of MRI image is important. Classification of Brain Tumor through segmented MR images, is a difficult task due to complexity and alteration in Tumor tissue characteristics like its location, size, gray level intensities and shape. Nowadays due to increasing Tumor cases it is difficult to examine all the reports manually also it sometimes becomes hazardous for a patient due to delay in the detection of the Tumor or the right time required for its surgery. In order to eradicate this problem an intelligent system is required for the detection and classification of brain Tumor automatically. Intelligence can be generally described as the ability to perceive information and retain it as knowledge to be applied towards adaptive behaviors within an environment or context. We propose a method which can automatically consider the MR images as an input and further analyze and process the input image and classify according to its presence and absence along with the type of Tumor detected. This can be done using two machine learning based techniques like neural networks and deep learning which can be used to solve many real-world problems.

Brain Tumor, MR Images, Neural Networks, Deep Learning, Intelligent System.

"Detection and Classification of Brain Tumor Using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.26-33, April-2019, Available :http://www.jetir.org/papers/JETIR1904C06.pdf

"Detection and Classification of Brain Tumor Using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp26-33, April-2019, Available at : http://www.jetir.org/papers/JETIR1904C06.pdf