Comparison of 3D Texture-based Image Descriptors in
Fluorescence Microscopy

D 2014

Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy

MAJTNER, Tomáš and David SVOBODA

Basic information

Original name

Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy

Authors

MAJTNER, Tomáš (703 Slovakia, guarantor, belonging to the institution) and David SVOBODA (203 Czech Republic, belonging to the institution)

Edition

Switzerland, 16th International Workshop on Combinatorial Image Analysis (IWCIA) 2014, p. 186-195, 10 pp. 2014

Publisher

Springer International Publishing

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/14:00073552

Organization unit

Faculty of Informatics

ISBN

978-3-319-07147-3

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-07148-0_17

Keywords in English

3D images; Texture descriptors; Fluorescence microscopy; Local Binary Patterns

Abstract

V originále

In recent years, research groups concentrate still 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 requires also 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 very strong approach with the classification accuracy more than 99% on selected group of 3D biomedical images.

Links

GBP302/12/G157, research and development project

Name: Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii

Investor: Czech Science Foundation

MUNI/A/0855/2013, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace III. (Acronym: FI MAV III.)

Investor: Masaryk University, Category A

Citovat

MAJTNER, Tomáš and David SVOBODA. Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy. In Reneta P. Barneva, Valentin E. Brimkov, Josef Šlapal. 16th International Workshop on Combinatorial Image Analysis (IWCIA) 2014. Switzerland: Springer International Publishing, 2014, p. 186-195. ISBN 978-3-319-07147-3. Available from: https://dx.doi.org/10.1007/978-3-319-07148-0_17.

@inproceedings{1173483,
   author = {Majtner, Tomáš and Svoboda, David},
   address = {Switzerland},
   booktitle = {16th International Workshop on Combinatorial Image Analysis (IWCIA) 2014},
   doi = {http://dx.doi.org/10.1007/978-3-319-07148-0_17},
   editor = {Reneta P. Barneva, Valentin E. Brimkov, Josef Šlapal},
   keywords = {3D images; Texture descriptors; Fluorescence microscopy; Local Binary Patterns},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Switzerland},
   isbn = {978-3-319-07147-3},
   pages = {186-195},
   publisher = {Springer International Publishing},
   title = {Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy},
   url = {http://link.springer.com/chapter/10.1007/978-3-319-07148-0_17},
   year = {2014}
}

TY  - JOUR
ID  - 1173483
AU  - Majtner, Tomáš - Svoboda, David
PY  - 2014
TI  - Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy
PB  - Springer International Publishing
CY  - Switzerland
SN  - 9783319071473
KW  - 3D images
KW  - Texture descriptors
KW  - Fluorescence microscopy
KW  - Local Binary Patterns
UR  - http://link.springer.com/chapter/10.1007/978-3-319-07148-0_17
L2  - http://link.springer.com/chapter/10.1007/978-3-319-07148-0_17
N2  - In recent years, research groups concentrate still 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 requires also 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 very strong approach with the classification accuracy more than 99% on selected group of 3D biomedical images.
ER  -

MAJTNER, Tomáš and David SVOBODA. Comparison of 3D Texture-based Image Descriptors in Fluorescence Microscopy. In Reneta P. Barneva, Valentin E. Brimkov, Josef Šlapal. \textit{16th International Workshop on Combinatorial Image Analysis (IWCIA) 2014}. Switzerland: Springer International Publishing, 2014, p.~186-195. ISBN~978-3-319-07147-3. Available from: https://dx.doi.org/10.1007/978-3-319-07148-0\_{}17.

Detailed Information on Publication Record