Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/3418
DC FieldValueLanguage
dc.contributor.authorStarcevic D.en
dc.contributor.authorOstojić, Vladimiren
dc.contributor.authorPetrović, Višnjaen
dc.date.accessioned2019-09-23T10:27:39Z-
dc.date.available2019-09-23T10:27:39Z-
dc.date.issued2017-01-13en
dc.identifier.isbn9788674666494en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/3418-
dc.description.abstract© 2016 IEEE. In this paper we propose a method for automatic collimation border rotation angle detection. Algorithm utilizes pooling of image gradients based on their orientations to form a histogram of oriented gradients (HOG) with the goal of determining the dominant gradient orientation in the image as collimation border rotation angle. To avoid accumulation of lower magnitude gradients only a percentage of the highest magnitude gradients was used during HOG calculation. Algorithm was evaluated on image database consisting of 244 real clinical images. Performance was measured through mean absolute error (MAE) between manually determined collimation field rotation angle and the angle estimated by the algorithm. Algorithm has achieved MAE of 0.388 degrees when using 21 % of the highest magnitude gradients.en
dc.relation.ispartof24th Telecommunications Forum, TELFOR 2016en
dc.titleAutomatic evaluation of collimation field rotation angle in digital radiographic imagesen
dc.typeConference Paperen
dc.identifier.doi10.1109/TELFOR.2016.7818801en
dc.identifier.scopus2-s2.0-85013668118en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85013668118en
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:FTN Publikacije/Publications
Show simple item record

Page view(s)

19
Last Week
9
Last month
0
checked on May 10, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.