Brain tumor segmentation and its area calculation in brain MR images using K-mean clustering and Fuzzy C-mean
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Product Description
Abstract:
Brain
tumor identification is really challenging task in early stages of life. But
now it became advanced with deep-learning. Now a day’s issue of brain tumor
automatic identification is of great interest. In Order to detect the brain
tumor of a patient we consider the data of patients like MRI images of a
patient’s brain. Here our problem is to identify whether tumor is present in
patients brain or not. It is very important to detect the tumors at starting
level for a healthy life of a patient. Finally
deep neural networks classifier is applied then
result image will compared with the dataset images and it will display whether
it is benign or malignant.
Proposed System:
We are providing new methods of MRI images of Brain of a patient. The images are pre processed and
further segmented for the required feature. Then
feature Extraction is done for the images by GLCM features. Region of interest (ROI) segmentations
is applied in order to identify the affected portion of tumor.
Here the threshold required for segmenting adjusts itself according to the
segmented area and position. Finally classification
applied through a deep neural networks then result
image will compared with the dataset images and it will display whether it is
benign or malignant.
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