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2019 | OriginalPaper | Buchkapitel

Tumor Detection and Analysis Using Improved Fuzzy C-Means Algorithm

verfasst von : R. Swathika, T. Sree Sharmila, M. Janani Bharathi, S. Jacindha

Erschienen in: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Verlag: Springer International Publishing

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Abstract

Formation of abnormal cells in brain serves the major cause of tumor. With estimated deaths of 229,000 as of 2015, it has become an issue to be dealt. The less awareness of brain tumor owes to lots of unaccounted deaths. Thus, we aim in developing an app which could serve the purpose of detecting the tumor and giving additional information related to the detected tumor. This app takes in an MRI image and does preprocessing followed by clustering, segmentation, and binarization. The preprocessing involves the conversion of the image into grayscale and noise filtering. We aim at using improved Fuzzy c-means algorithm for clustering and segmentation. Binarization mainly aims at calculating the tumor size useful for further analysis. The improved fuzzy c-means algorithm overcomes the various constraints of k-means algorithm such as time complexity, processing of noisy images, and memory space.

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Literatur
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Metadaten
Titel
Tumor Detection and Analysis Using Improved Fuzzy C-Means Algorithm
verfasst von
R. Swathika
T. Sree Sharmila
M. Janani Bharathi
S. Jacindha
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-00665-5_109

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