This paper presents an efficient region based segmentation technique for detecting pathological tissues (Tumor &
Edema) of brain using fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. This work
segments FLAIR brain images for normal and pathological tissues based on statistical features and wavelet transform
coefficients using k-means algorithm. The image is divided into small blocks of 4×4 pixels. The k-means algorithm is
used to cluster the image based on the feature vectors of blocks forming different classes representing different regions in
the whole image. With the knowledge of the feature vectors of different segmented regions, supervised technique is used
to train Artificial Neural Network using fuzzy back propagation algorithm (FBPA). Segmentation for detecting healthy
tissues and tumors has been reported by several researchers by using conventional MRI sequences like T1, T2 and PD
weighted sequences. This work successfully presents segmentation of healthy and pathological tissues (both Tumors and
Edema) using FLAIR images. At the end pseudo coloring of segmented and classified regions are done for better human
visualization.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.