Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/11648
Title: | Improved quantification of bone remodelling by utilizing fuzzy based segmentation | Authors: | Lindblad J. Sladoje N. Ćurić V. Sarve H. Johansson C. Borgefors G. |
Issue Date: | 9-Nov-2009 | Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Abstract: | We present a novel fuzzy theory based method for the segmentation of images required in histomorphometrical investigations of bone implant integration. The suggested method combines discriminant analysis classification controlled by an introduced uncertainty measure, and fuzzy connectedness segmentation method, so that the former is used for automatic seeding of the later. A thorough evaluation of the proposed segmentation method is performed. Comparison with previously published automatically obtained measurements, as well as with manually obtained ones, is presented. The proposed method improves the segmentation and, consequently, the accuracy of the automatic measurements, while keeping advantages with respect to the manual ones, by being fast, repeatable, and objective. © 2009 Springer Berlin Heidelberg. | URI: | https://open.uns.ac.rs/handle/123456789/11648 | ISBN: | 3642022294 | ISSN: | 03029743 | DOI: | 10.1007/978-3-642-02230-2_77 |
Appears in Collections: | Naučne i umetničke publikacije |
Show full item record
SCOPUSTM
Citations
2
checked on Aug 12, 2023
Page view(s)
6
Last Week
2
2
Last month
0
0
checked on May 10, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.