International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 01 | Jan 2023 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 546 Automated Intracranial Neoplasm Detection Using Convolutional Neural Networks Mr. P. Veeresh Kumar 1 , N. Geetha Gayathri 2 , G. Harika 3 , Ch. Sai Poojitha 4 , G. Vyshnavi 5 T. Lakshmi 6 1 Associate Professor Department of Information Technology, KKR & KSR Institute Of Technology And Sciences(A), Guntur, India 2,3,4,5,6 Undergraduate Students ,Department of Information Technology , KKR & KSR Institute Of Technology And Sciences(A), Guntur, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - A brain tumor is nothing but an abnormal collection of cells in the intracranial. The skull that surrounds the brain is very hard, so when a tumor grows inside the brain, it puts pressure on the skull and can cause serious damage. It is regarded as one of the most dangerous diseases in both children and adults. About 11,700 people are diagnosed with brain tumors each year. It accounts for 85–90% of all central nervous system tumors. The 5-year survival rate for malignant brain tumors is approximately 34% for men and 36% for women. Accurate diagnosis, detection of brain tumors , and early initiation of appropriate treatment are essential to prolonging a patient's life expectancy. Brain tumor segmentation is one of the most important and laborious tasks in the field of medical imaging. Manual classification with human assistance can lead to inaccurate predictions and diagnoses. Additionally, this is a daunting task when there is a large amount of data that needs to be supported. Brain tumors are highly variable in appearance, and there are similarities between tumor tissue and normal tissue, thus making the extraction of tumor regions from images difficult. There are different types of imaging tests, such as X-rays, MRIs, and CT scans, used to detect brain tumors. In this study, computed tomography (CT) scan images are used to identify brain tumors. Deep learning (DL) is the latest technology that provides more efficient results in detection and classification. In this paper, a model is developed by detecting tumors using a convolutional neural network. In our study, CNN achieved 97.87% accuracy. Key Words: Brain Tumor, Magnetic Resonance Image (MRI), Convolutional Neural Networks (CNN), Deep Learning, Tensor Flow, Keras. 1. INTRODUCTION We use medical imaging technology to get a glimpse inside the human body. The most difficult task is to diagnose and classify tumors or cancers. According to statistics, brain tumors are one of the most important types of cancer in terms of mortality. The International Agency for Research on Cancer (IARC) reports that worldwide, more than one million people are diagnosed with 4,444 brain tumors each year, and the mortality rate is steadily increasing year by year. Those under the age of 34 To date, doctors have implemented over 4,444 advanced methods to identify more painful tumors in patients. Using CT (computed tomography) and MRI (magnetic resonance imaging) scans, doctors can now dissect abnormalities in different parts of the body. Brain tumors have recently gained momentum due to the increased demand for labour savings and the clinical evaluation of large amounts of medical data. This type of image processing and analysis involves complex calculations of data as well as visualizing and understanding that data. Brain tumors can originate from abnormal, precancerous, cancerous, harmful, harmless, or non-cancerous cells that form in the brain. He divides malignant tumors into two types: those that originate in the brain and subsequent cancerous growths that can spread to different areas of the human body. Under these conditions, cancer metastasizes within the patient's body and is said to have a very low survival rate and a high mortality rate. 1.1 Brain Tumor The brain is a soft tissue mass that resembles a sponge that is covered in bone. The brain is lined with a delicate layer of tissue, including cerebrospinal fluid. Between the brain and the ventricles, there is cerebrospinal fluid. The cerebrum, cerebellum, and brainstem are the three components that make up the brain. The brain reacts to external stimuli. The cerebellum maintains the body's equilibrium. The brain and spinal cord are linked by the brainstem. A brain tumor is recognized as an overgrowth of the numerous cells that make up the brain. Primary and secondary cells are both present. While secondary cells are spared by metastasis from other parts of the body to the brain, primary cells come from the brain itself. Some metastases spread rapidly. Some metastases spread fairly quickly and exhibit symptoms like seizures, speech difficulties, nausea, and blurred vision. It can be fatal if not treated in a timely manner. This is due to EDA, which is brought on by decreased blood flow and the subsequent deterioration of healthy tissue as a result of the skull's constrained interior and growing intracranial pressure. Electronic healthcare systems and magnetic field information technology aid clinical professionals in giving patients better care. A brain tumor can affect other nearby