Cancer Diagnosis using Image Processing and Artificial Intelligence based techniques

A brain tumor is a growth of abnormal cells in the tissues of the brain. The brain tumor is affecting many people worldwide. It is not only limited with the old age people but also detected in the early age. Early detection of the brain tumor is possible with the advancement of machin

Project Title

Cancer Diagnosis using Image Processing and Artificial Intelligence based techniques

Project Area of Specialization

Artificial Intelligence

Project Summary

A brain tumor is a growth of abnormal cells in the tissues of the brain. The brain tumor is affecting many people worldwide. It is not only limited with the old age people but also detected in the early age. Early detection of the brain tumor is possible with the advancement of machine learning (ML) and image processing. Magnetic Resonance Imaging (MRI) is the most effective and extensively used technique for brain tumor detection as it provides greater contrast images of the brain. However the huge amount of data generated by MRI scan complicates manual classification of tumor vs. non-tumor in a particular time. Hence trusted and automatic classification schemes such as Neural Networks (NN) are highly effective for the process of classification. The purpose of this project is to develop software to detect brain tumor using Machine Learning and Image Processing based techniques.

Project Objectives

• To facilitate doctors to diagnose cancer using image processing and machine learning based software.
• To save doctor’s time for identification of the brain tumor in contrast to manual process.
• To eliminate any possibility of false detection when identifying brain tumors.

Project Implementation Method

Current Cancer diagnosis techniques are performed using the  conventional  methods  based  on  human  experience  and  this  increases  the  possibility  of  false detection  when  identifying  brain  tumors.  Present tools and methods to analyze tumors and their behavior have become more prevalent. Image processing and machine learning based techniques can be used to name brain tumors. Image processing is a method to convert an image into digital form & perform some operation on it, in order to get an enhanced image or to extract some useful information from it.

Cancer diagnostic model is a desktop application that will use following image processing and machine learning based techniques to detect brain tumor and further characterize what type of tumor it is either cancerous or non-cancerous.

• Pre-processing
• Segmentation
• Feature Extraction
• Classification

Benefits of the Project

It will save doctor’s time for identification of the brain tumor in contrast to manual process and eliminate any possibility of false detection when identifying brain tumors which will prove to be life saving for many patients.

It is fully automated cancer diagnostic tool which will speed up the process of cancer diagnosis and Patients can be given early medication which is essential for their treatment.

Technical Details of Final Deliverable

Final Deliverable will be a desktop application for Doctors. Apllication will take MRI images of a patient as input and analyze the MRI images using the trained model and generate analysis report that whether the patient has a tumor or not, if yes, then further characterize what type of tumor it is ,either cancerous or non-cancerous.

Final Deliverable of the Project

Software System

Type of Industry

IT , Health

Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com