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

D 2014

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

MAJTNER, Tomáš a David SVOBODA

Základní údaje

Originální název

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

Autoři

MAJTNER, Tomáš (703 Slovensko, garant, domácí) a David SVOBODA (203 Česká republika, domácí)

Vydání

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

Nakladatel

Springer International Publishing

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Impakt faktor

Impact factor: 0.402 v roce 2005

Kód RIV

RIV/00216224:14330/14:00073552

Organizační jednotka

Fakulta informatiky

ISBN

978-3-319-07147-3

ISSN

DOI

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

Klíčová slova anglicky

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

Štítky

best, cbia-web

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 9. 1. 2015 15:37, RNDr. Ing. Bc. Tomáš Majtner, Ph.D.

Anotace

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.

Návaznosti

GBP302/12/G157, projekt VaV

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

Investor: Grantová agentura ČR, Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii

MUNI/A/0855/2013, interní kód MU

Název: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace III. (Akronym: FI MAV III.)

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace III., DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

Citovat

MAJTNER, Tomáš a 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, s. 186-195. ISBN 978-3-319-07147-3. Dostupné z: 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 a 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, s.~186-195. ISBN~978-3-319-07147-3. Dostupné z: https://dx.doi.org/10.1007/978-3-319-07148-0\_{}17.

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