Abstract

Brain tumor is considered as one of the aggressive diseases, among children and adults. Brain tumors account for 85 to 90 percent of all primary Central Nervous System(CNS) tumors. Every year, around 11,700 people are diagnosed with a brain tumor. The 5-year survival rate for people with a cancerous brain or CNS tumor is approximately 34 percent for men and 36 percent for women. BrainTumors are classified as: Benign Tumor, Malignant Tumor, Pituitary Tumor, etc. Proper treatment planning and accurate diagnostics should be implemented to improve life expectancy of the patients. The best technique to detect brain tumor is Magnetic Resonance Imaging (MRI). Huge amount of data images are generated through the scans. These images are examined by the radiologist. Manual examination can be error prone due to the level of complexities involved in brain tumors and their properties. Application of automated classification techniques using Machine Learning(ML) and Artificial Intelligence(AI) has consistently shown higher accuracy than manual classification.

Hence, we propose performing detection and classification by using Deep Learning Algorithms using Convolution Neural Network (CNN) and Artificial Neural Network (ANN) to achieve higher accuracy. The MRI images are classified using different ’Deep Learning Models of ANN and CNN’. These models have permutations and combinations of different ’Network Parameters’. The model with the highest accuracy is selected and deployed. The aim of the project is to achieve higher accuracy and reliability for real world MRI data using AI and ML domain knowledge. Further to accurately indicate positional change in tumor and to provide some suggestions for treatment by providing ease of access of the software through cloud and mobile applications, web browsers platforms.

Objectives

Tumor Detection

Using Neural Networks to identify if the MRI as tumor present or not.

Tumor Classification

To classify tumors using Deep Learning Classification Algorithms.

Tumor Segmentation

To segrigate tumor from MRI.

Tumor Movements

To identify tumor positional changes.

Best Model Statistics

Here we present the statistics of the deployed model.

  • Accuracy

  • Loss(*10)

  • Validation Loss(*10)

  • Validation Accuracy

Categories

Here we put information of IV classes.

No Tumor

The Brain scan is normal. No Tumor is detected.

Glioma Tumor

A glioma is a type of tumor that starts in the glial cells of the brain or the spine. Gliomas comprise about 30 percent of all brain tumors and central nervous system tumours, and 80 percent of all malignant brain tumours.

Read More »

Malignant Tumor

A malignant tumor contrasts with a non-cancerous benign tumor in that a malignancy is not self-limited in its growth, is capable of invading into adjacent tissues, and may be capable of spreading to distant tissues.

Read More »

Pituary Tumor

Pituitary adenomas are tumors that occur in the pituitary gland. Pituitary adenomas are generally divided into three categories dependent upon their biological functioning: benign adenoma, invasive adenoma, and carcinomas.

Read More »