Survey On AI Based Approach for Classification of Multi Grade Tumour in Human Brain
Author(s):
Dheeraj D, Pooja Tapas, Rithika R, Nithish P, Rashmi M
Keywords:
CNN, Deep Learning, Medical Image
Abstract
The categorization of brain tumour images is an important step in medical image processing. Doctors can use it to develop precise diagnoses and treatment strategies. One of the most common imaging techniques for studying brain tissue is magnetic resonance imaging (MR imaging). Carrying out this research, we will be further be engaging on the implementation of the three models which includes, U-net, VGG-16 and AlexNet for small, large and very large dataset, implementing the same on GPU, evaluating the performance of all the three models to compare the same and notice the contrast between the performance of the models, optimization of the parameters to assess their performance and hence, record the best performance model. The main aim of the project is to provide an environment where doctors can view and interact with patient specific anatomical form, functions and flow for improved diagnosis and more precise surgical planning. Surgeons will be able to analyse their patients' anatomy in more detail thanks to augmented reality. Without needing to operate, surgeons will be able to see bones, muscles, and interior organs. This could also aid them in determining where injections and incisions should be made, which could be useful in an emergency.
Article Details
Unique Paper ID: 154551

Publication Volume & Issue: Volume 8, Issue 11

Page(s): 506 - 510
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