dc.contributor.author | ABDULRAQEB, A.R. | |
dc.contributor.author | SUSHKOVA, L.T. | |
dc.date.accessioned | 2019-10-23T11:05:13Z | |
dc.date.available | 2019-10-23T11:05:13Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | ABDULRAQEB, A.R., SUSHKOVA, L.T. Proposed segmentation algorithm for mri brain tumor images. In: Health Technology Management. Book of abstracts: proc. of the 3rd intern. conf., October 6-17, 2016. Chişinău, 2016, p. 70. ISBN 978-9975-51-774-4 | en_US |
dc.identifier.isbn | 978-9975-51-774-4 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/5106 | |
dc.description | Abstract | en_US |
dc.description.abstract | A great work in the field of medical imaging research was focused on brain tumors segmentation in the recent years [1]. In many Hospitals, brain tumor measurements are obtained by magnetic resonance images (MRI) radiologists, who measure the mass of the tumor manually by using widely available imaging software. Such approach is a time consuming task and leads to large variations in operator performance. Several methods were proposed and developed for accurate segmentation [2-4] such as thresholding, region based, edge based, and clustering methods etc. In this work, thresholding, region growing and proposed method (region growing + active contour) were experimented on two datasets (the first one includes 18 images from a specialized clinic in Vladimir and the second data set of 52 images from a specialized clinic in Riyadh). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Tehnica UTM | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | brain tumor measurements | en_US |
dc.subject | magnetic resonance images | en_US |
dc.title | Proposed segmentation algorithm for mri brain tumor images | en_US |
dc.type | Article | en_US |
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