Efficient k-NN based HEp-2 cells classifier

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00073423" target="_blank" >RIV/00216224:14330/14:00073423 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.patcog.2013.09.021" target="_blank" >http://dx.doi.org/10.1016/j.patcog.2013.09.021</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.patcog.2013.09.021" target="_blank" >10.1016/j.patcog.2013.09.021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Efficient k-NN based HEp-2 cells classifier

Popis výsledku v původním jazyce

Human Epithelial (HEp-2) cells are commonly used in the Indirect Immunofluorescence (IIF) tests to detect autoimmune diseases. The diagnosis consists of searching and classification to specific patterns created by Anti-Nuclear Antibodies (ANAs) in the patient serum. Evaluation of the IIF test is mostly done by humans, which means that it is highly dependent on the experience and expertise of the physician. Therefore, a significant amount of research has been focused on the development of computer aideddiagnostic systems which could help with the analysis of images from microscopes. This work deals with the design and development of HEp-2 cells classifier. The classifier is able to categorize pre-segmented images of HEp-2 cells into 6 classes. The coreof this engine consists of the following image descriptors: Haralick features, Local Binary Patterns, SIFT, surface description and a granulometry-based descriptor. These descriptors produce vectors that form metric spaces.

Název v anglickém jazyce

Efficient k-NN based HEp-2 cells classifier

Popis výsledku anglicky

Human Epithelial (HEp-2) cells are commonly used in the Indirect Immunofluorescence (IIF) tests to detect autoimmune diseases. The diagnosis consists of searching and classification to specific patterns created by Anti-Nuclear Antibodies (ANAs) in the patient serum. Evaluation of the IIF test is mostly done by humans, which means that it is highly dependent on the experience and expertise of the physician. Therefore, a significant amount of research has been focused on the development of computer aideddiagnostic systems which could help with the analysis of images from microscopes. This work deals with the design and development of HEp-2 cells classifier. The classifier is able to categorize pre-segmented images of HEp-2 cells into 6 classes. The coreof this engine consists of the following image descriptors: Haralick features, Local Binary Patterns, SIFT, surface description and a granulometry-based descriptor. These descriptors produce vectors that form metric spaces.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GBP302%2F12%2FG157" target="_blank" >GBP302/12/G157: Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PATTERN RECOGNITION

ISSN

0031-3203

e-ISSN

—

Svazek periodika

47

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

2409-2418

Kód UT WoS článku

000334978100012

EID výsledku v databázi Scopus

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