Comparison of 3D texture-based image descriptors in fluorescence microscopy

Tomáš Majtner, David Svoboda

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstrakt

In recent years, research groups pay even more attention on 3D images, especially in the field of biomedical image processing. Adding another dimension enables to capture the entire object. On the other hand, handling 3D images also requires new algorithms, since not all of them can be modified for higher dimensions intuitively. In this article, we introduce a comparison of various implementations of 3D texture descriptors presented in the literature in recent years. We prepared an unified environment to test all of them under the same conditions. From the results of our tests we came to conclusion, that 3D variants of LBP in the combination with k-NN classifier are a very strong approach with the classification accuracy more than 99% on selected group of 3D biomedical images.

OriginalsprogEngelsk
TitelCombinatorial Image Analysis - 16th International Workshop, IWCIA 2014, Proceedings
Antal sider10
ForlagSpringer VS
Publikationsdato1. jan. 2014
Sider186-195
ISBN (Trykt)9783319071473
DOI
StatusUdgivet - 1. jan. 2014
Udgivet eksterntJa
Begivenhed16th International Workshop on Combinatorial Image Analysis, IWCIA 2014 - Brno, Tjekkiet
Varighed: 28. maj 201430. maj 2014

Konference

Konference16th International Workshop on Combinatorial Image Analysis, IWCIA 2014
LandTjekkiet
ByBrno
Periode28/05/201430/05/2014
SponsorBrno University of Technology
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind8466 LNCS
ISSN0302-9743

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