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AuthorDakua, Sarada Prasad
AuthorAbinahed, Julien
AuthorAl-Ansari, Abdulla
AuthorBermejo, Pablo Garcia
AuthorZakaria, Ayaman
AuthorAmira, Abbes
AuthorBensaali, Faycal
Available date2020-08-12T09:32:57Z
Publication Date2019
Publication NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ResourceScopus
URIhttp://dx.doi.org/10.1007/978-3-030-13835-6_2
URIhttp://hdl.handle.net/10576/15485
AbstractCerebral aneurysms are among most prevalent and devastating cerebrovascular diseases of adult population worldwide. The resulting sequelae of untimely/inadequate therapeutic intervention include sub-arachnoid hemorrhage. Geometric modeling of aneurysm being the first step in the treatment planning, the scientists therefore focus more on segmentation of aneurysm rather than its detection. A successful aneurysm detection among the bunch of vessels would certainly facilitate and ease the segmentation process. In this work, we present a novel method for aneurysm detection; the key contributions are: contrast enhancement of input image using stochastic resonance concept in wavelet domain, adaptive thresholding, and modified Hough Circle Transform. Experimental results show that the proposed method is efficient in detecting the location and type of aneurysm.
SponsorThis work was partly supported by NPRP Grant #NPRP 5-792-2-328 from the Qatar National Research Fund (a member of the Qatar Foundation).
Languageen
PublisherSpringer Verlag
SubjectCerebral aneurysm
Detection
Hough transform
TitleA method towards cerebral aneurysm detection in clinical settings
TypeConference Paper
Pagination15-Aug
Volume Number11379


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