Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

Nandita Pradhan; A. K. Sinha

doi:10.1117/12.770378

17 March 2008 Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

Nandita Pradhan, A. K. Sinha

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 69151W (2008) https://doi.org/10.1117/12.770378
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

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.

Citation Download Citation

Nandita Pradhan and 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

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KEYWORDS

Image segmentation

Tumors

Brain

Tissues

Magnetic resonance imaging

Neuroimaging

Fuzzy logic

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