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Publication Type : Conference Paper
Publisher : Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018
Source : Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018, Institute of Electrical and Electronics Engineers Inc., p.18-22 (2018)
ISBN : 9781538635216
Keywords : Brain, Brain tumor detections, Cells, Cytology, Image segmentation, Image thresholding, K - means clustering, Level-set segmentations, Magnetic Resonance Imaging, Mathematical morphology, Morphological operations, Performance matrices, Precision and recall, Segmentation techniques, Tumors
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2018
Brain Tumor is the unconstrained growth of bizarre cells in brain. In this work, dicom Magnetic Resonance Image MRI is taken as an input and tried to extract tumor cells from the input image. Pre-processing technique is used to remove noise from image. To this image, k-means clustering is applied and from this clustered image, skull was removed using morphological operations to identify tumor cells easily. Finally, image thresholding is applied to this image followed by levelset segmentation to extract tumor cells. Performance matrices like true positive TP, true negative TN, false positive FP, false negative FN, precision and recall to measure the accuracy of our results, is also evaluated. © 2018 IEEE.
Cite this Research Publication : D. Reddy, ,, ,, Bhavana V., and Krishnappa, H. K., “Brain Tumor Detection Using Image Segmentation Techniques”, in Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018, 2018, pp. 18-22.