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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15711
Title: Automatic segmentation of intracerebral hemorrhage from brain CT images
Authors: Gautam A.
Raman B.
Tanveer M.
Pachori R.B.
Published in: Proceedings of Advances in Intelligent Systems and Computing
Abstract: Intracerebral hemorrhage (ICH) diagnosis is a neurological deficit that can occur in the patients suffering from high blood pressure and head trauma. Manual segmentation of ICH is tedious and operator dependent, therefore the purpose of this study is to present a robust fully automated system for hemorrhage detection from Computed Tomography (CT) scan images. The proposed method is based on White Matter Fuzzy c-Means (WMFCM) clustering and wavelet-based thresholding. The suggested method starts with the removal of components which do not look like brain tissues including skull by using a new WMFCM technique. After brain extraction, a new segmentation technique based on wavelet thresholding is used for detection and localization of hemorrhagic stroke. The proposed segmentation method is fast and accurate where standard evaluation metrics like dice similarity coefficients, Jaccard distance, Hausdorff distance, precision, recall, and F1 score are used to measure the accuracy of the proposed algorithm. Our method is demonstrated on a dataset of 20 brain computed tomography (CT) images suffered ICH and results obtained are compared with the ground truth of images. We found that our method can detect ICH with an average dice similarity of 0.82 and perform better as compared to standard fuzzy c-means (FCM) and spatial FCM (SFCM) clustering methods. © Springer Nature Singapore Pte Ltd 2019.
Citation: Proceedings of Advances in Intelligent Systems and Computing, (2019), 753- 764
URI: https://doi.org/10.1007/978-981-13-0923-6_64
http://repository.iitr.ac.in/handle/123456789/15711
Issue Date: 2019
Publisher: Springer Verlag
Keywords: Computed tomography (CT)
Fuzzy c-means
Intracerebral hemorrhage (ICH)
Segmentation
ISBN: 9789811309229
ISSN: 21945357
Author Scopus IDs: 57196216030
23135470700
Author Affiliations: Gautam, A., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Raman, B., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Corresponding Author: Gautam, A.; Department of Computer Science and Engineering, Indian Institute of Technology RoorkeeIndia; email: anga3.dcs2015@iitr.ac.in
Appears in Collections:Conference Publications [CS]

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