ABSTRACT
PROJECT OUTPUT
Image processing is an active research area in which medical image
processing is a highly challenging field. Medical imaging techniques are
used to image the inner portions of the human body for medical
diagnosis. Brain tumor is a serious life altering disease condition.
Image segmentation plays a significant role in image processing as it
helps in the extraction of suspicious regions from the medical images.
In this paper we have proposed segmentation of brain MRI image using
K-means clustering algorithm followed by morphological filtering which
avoids the mis-clustered regions that can inevitably be formed after
segmentation of the brain MRI image for detection of tumor location. In
this paper, we present a system based on gabor filter based enhancement
technique and feature extraction techniques using texture based
segmentation and SOM (Self Organization Map) which is a form of
Artificial Neural Network (ANN) used to analyze the texture features
extracted. SOM determines which texture feature has the ability to
classify benign, malignant and normal cases. Watershed segmentation
technique is used to classify cancerous region from the non cancerous
region.
PROJECT OUTPUT
Contact:
Mr. Roshan P. Helonde
Mobile / WhatsApp:+91-7276355704
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