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17 March 2008Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN
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.
Nandita Pradhan andA. K. Sinha
"Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69151W (17 March 2008); https://doi.org/10.1117/12.770378
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Nandita Pradhan, A. K. Sinha, "Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN," Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69151W (17 March 2008); https://doi.org/10.1117/12.770378