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Title: A Modified FCM-Based Brain Lesion Segmentation Scheme for Medical Images
Authors: Gautam A.
Sadhya D.
Raman, Balasubramanian
Chaudhuri B.B.
Nakagawa M.
Khanna P.
Kumar S.
Published in: Advances in Intelligent Systems and Computing
3rd International Conference on Computer Vision and Image Processing, CVIP 2018
Abstract: Segmentation of brain lesion from medical images is a critical problem in the present day. In this work, we have proposed a new distance metric for fuzzy clustering based classification of different brain regions via acquiring accurate lesion structures. The modified distance metric segments the images into different regions by calculating the distances between the cluster centers and object elements, and subsequently classify them via fuzzy clustering. The proposed method can effectively remove noise from the images, which results in a better homogeneous classification of the image. Our method can also accurately segment stroke lesion where the results are near to the ground truth of the stroke lesion. The performance of our method is evaluated on both magnetic resonance images (MRI) and computed tomography (CT) images of brain. The obtained results indicate that our method performs better than the standard fuzzy c-means (FCM), spatial FCM (SFCM), kernelized FCM methods (KFCM), and adaptively regularized kernel-based FCM (ARKFCM) schemes. © 2020, Springer Nature Singapore Pte Ltd.
Citation: Advances in Intelligent Systems and Computing (2020), 1024: 149-159
Issue Date: 2020
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Brain stroke
Fuzzy c-means (FCM)
ISBN: 9.78981E+12
ISSN: 21945357
Author Scopus IDs: 57196216030
Author Affiliations: Gautam, A., Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Sadhya, D., Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Raman, B., Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Funding Details: We thank Institute Human Ethics Committee (IHEC) of Indian Institute of Technology Roorkee, India for allowing us to collect the CT image dataset of hemorrhagic stroke with its ground truth information from Himalayan Institute of Medical Sciences (HIMS), Dehradun, Uttarakhand, India. The consent to obtain CT scan images of patients has already been taken by the radiologists of HIMS. We also thank Dr. Shailendra Raghuwanshi, Head of Radiology Department, HIMS for providing us his useful suggestions.
Corresponding Author: Gautam, A.; Indian Institute of Technology RoorkeeIndia; email:
Appears in Collections:Conference Publications [CS]

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