Classification of tumor epithelium and stroma in colorectal cancer based on discrete tchebichef moments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00337840" target="_blank" >RIV/68407700:21230/16:00337840 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/content/pdf/10.1007%2F978-3-319-31808-0_10.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007%2F978-3-319-31808-0_10.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-31808-0_10" target="_blank" >10.1007/978-3-319-31808-0_10</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of tumor epithelium and stroma in colorectal cancer based on discrete tchebichef moments

Popis výsledku v původním jazyce

Colorectal cancer is a major cause of mortality. As the disease progresses, adenomas and their surrounding tissue are modified. Therefore, a large number of samples from the epithelial cell layer and stroma must be collected and analyzed manually to estimate the potential evolution and stage of the disease. In this study, we propose a novel method for automatic classification of tumor epithelium and stroma in digitized tissue microarrays. To this end, we use discrete Tchebichef moments (DTMs) to characterize tumors based on their textural information. DTMs are able to capture image features in a non-redundant way providing a unique description. A support vector machine was trained to classify a dataset composed of 1376 tissue microarrays from 643 patients with colorectal cancer. The proposal achieved 97.62% of sensitivity and 95% of specificity showing the effectiveness of the methodology.

Název v anglickém jazyce

Classification of tumor epithelium and stroma in colorectal cancer based on discrete tchebichef moments

Popis výsledku anglicky

Colorectal cancer is a major cause of mortality. As the disease progresses, adenomas and their surrounding tissue are modified. Therefore, a large number of samples from the epithelial cell layer and stroma must be collected and analyzed manually to estimate the potential evolution and stage of the disease. In this study, we propose a novel method for automatic classification of tumor epithelium and stroma in digitized tissue microarrays. To this end, we use discrete Tchebichef moments (DTMs) to characterize tumors based on their textural information. DTMs are able to capture image features in a non-redundant way providing a unique description. A support vector machine was trained to classify a dataset composed of 1376 tissue microarrays from 643 patients with colorectal cancer. The proposal achieved 97.62% of sensitivity and 95% of specificity showing the effectiveness of the methodology.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

CLIP 2015: Proceedings of the 4th MICCAIA Workshop on Clinical Image-Based Procedures

ISBN

978-3-319-31807-3

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

9

Strana od-do

79-87

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Munich

Datum konání akce

5. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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