Brain Tumor Boundary Detection by Edge Indication Map Using Bi-Modal Fuzzy Histogram Thresholding Technique from MRI T2-Weighted Scans
Автор: T. Kalaiselvi, P. Sriramakrishnan, P. Nagaraja
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 9 vol.8, 2016 года.
Бесплатный доступ
Tumor boundary detection is one of the challenging tasks in the medical diagnosis field. The proposed work constructed brain tumor boundary using bi-modal fuzzy histogram thresholding and edge indication map (EIM). The proposed work has two major steps. Initially step 1 is aimed to enhance the contrast in order to make the sharp edges. An intensity transformation is used for contrast enhancement with automatic threshold value produced by bimodal fuzzy histogram thresholding technique. Next in step 2 the EIM is generated by hybrid approach with the results of existing edge operators and maximum voting scheme. The edge indication map produces continuous tumor boundary along with brain border and substructures (cerebrospinal fluid (CSF), sulcal CSF (SCSF) and interhemispheric fissure) to reach the tumor location easily. The experimental results compared with gold standard using several evaluation parameters. The results showed better values and quality to proposed method than the traditional edge detection techniques. The 3D volume construction using edge indication map is very useful to analysis the brain tumor location during the surgical planning process.
Medical imaging, brain tumor, fuzzy histogram, edge indication map, 3D volume construction
Короткий адрес: https://sciup.org/15014015
IDR: 15014015
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