Brain Tumor Detection and classification using MRI and CT scanned Images


Category: Image Processing projects

Features included :

1. Source Code

2. Demo video

3. Synopsis

4. Report

5. Life time access

6. 20 days support after billing date


In today’s modern medical arena patients with
brain tumor are increasing rapidly with a fast pace and
above the par. Detection of brain tumor has become a
challenging task to compete with. In this paper an
automated method for detecting brain abnormalities and
tumor edema has been proposed using sobel edge detection
method. Various MRI images have been used as inputs
here. Here, first of all the pre-processing of image has been
done to cut out any discrepancy in it and then the image
has been smoothened using median filter. We have
proposed an appropriate method to find threshold value
using standard deviation and we get an intensity map. Now
we recomputed standard deviation for this intensity map.
Using this we will calculate an average intensity of the
pixels those are above this standard deviation. Finally, this
computed average intensity will be taken as the threshold
value to segment the tumor from the original MRI images.
The intensity value greater than and equal to the calculated
threshold value is set to 255 and less than is set to 0, this
segments our abnormal region which is tumor. At last, we
use sobel edge detector to identify the border of the tumor
region. The outcome of the proposed method improves
efficacy and accuracy for detection of brain tumors.

Watch Demo Video