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Title: A hybrid approach for the delineation of brain lesion from CT images
Authors: Gautam A.
Raman, Balasubramanian
Raghuvanshi S.
Published in: Biocybernetics and Biomedical Engineering
Abstract: Brain lesion segmentation from radiological images is the most important task in accurate diagnosis of patients. This paper presents a hybrid approach for the segmentation of brain lesion from computed tomography (CT) images based on the combination of fuzzy clustering using hyper tangent function as the robust kernel and distance regularized level set evolution (DRLSE) function as the edge based active contour method. Kernel based fuzzy clustering method divides the image into different regions. These regions can be used to find region of interest by using DRLSE algorithm to generate the optimal region boundary. The proposed method results in smooth boundary of the required regions with high accuracy of segmentation. In this paper, results are compared with standard fuzzy c-means (FCM) clustering, spatial FCM, robust kernel based fuzzy clustering (RFCM) and DRLSE algorithms. The performance of the proposed method is evaluated on CT scan images of hemorrhagic lesion, which shows that our method can segment brain lesion more accurately than the other conventional methods. © 2018 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Citation: Biocybernetics and Biomedical Engineering (2018), 38(3): 504-518
Issue Date: 2018
Publisher: PWN-Polish Scientific Publishers
Keywords: Brain lesion
Distance regularized level set evolution (DRLSE)
Fuzzy c-means
Kernel function
Level set
ISSN: 2085216
Author Scopus IDs: 57196216030
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
Raghuvanshi, S., Department of Radiology, Himalayan Institute of Medical Sciences, Jolly Grant, Dehradun, India
Funding Details: Funding provided by Indian Institute of Technology Roorkee, Roorkee, India under grant number MHC-02-23-200-428 to Anjali Gautam.
Corresponding Author: Gautam, A.; Indian Institute of Technology RoorkeeIndia; email:
Appears in Collections:Journal Publications [CS]

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