Clustering Of Brain MRI Image Using Datamining Algorithm
Data mining is the exploration and study of large quantities of data in order to discover original, valid,
understandable and potentially useful patterns in given data. Image data plays vital role in different systems like business,
education, medical, engineering, etc. Image mining comes under data mining where the extraction or mining knowledge is
from vast amount of image data. The image mining process involves analyzing the image data from different perception and
precise it into useful information by applying algorithms, tools and techniques. These algorithms and tools act as a way to
understand and study various relationships, associations and patterns which are hidden in the image data. Medical images
contain valuable information about human anatomy. New technologies help to capture and store images in different formats
in corresponding databases. These images need further extractions through which useful information can be obtained. The
extracted information is valuable as it can affect in an action, a decision, or an outcome. In this paper an attempt is made for
clustering brain MRI images using K-Means algorithm. A comparative study on clustering with K-Means algorithm and
Fuzzy C-Means algorithm was also done with the MRI image dataset.
Keywords- Fuzzy C-Means , Data mining , image clustering, K-Means, MRI.