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Guided by:
Dr. S Muruganandam
Emp Id: 100994
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The aim of our project is to develop a Deep Learning model which will be able to classify among different types of benign and malignant tumours using MRI imaging.
Classification of brain tumour images is an important aspect of medical image processing. It aids doctors in making precise diagnoses and treatment regimens. Magnetic resonance imaging (MRI) is one of the most often used imaging techniques for studying brain tissue. Using the MRI images that are stored in dataset we will try to classify the images into different types of tumours.
As we observe, some of the patients don't recover from the brain tumor because of late detection or it not being detected at all. Oberving this situation, we plan to create a deep learning model to efficiently detect brain tumours using datasets of MRIs.
Implementation of AI in the field of medical science using deep learning methods, helping to ease doctor's work and provide results efficiently to classify tumours, so that the patient's medication starts sooner, helping them to recover sooner than before.
The aim of our project is to develop a Deep Learning model which will help the doctors to efficiently classify among different types of benign and malignant tumours using MRI imaging.
This model will work as an API in the computer when the MRI images are provided to them as an input and then show the output immediately telling whether it is a tumour or not instead of doctors taking normally 5-7 days to confirm.