Classification of microscopy images of Langerhans islets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F14%3A00059764" target="_blank" >RIV/00023001:_____/14:00059764 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/14:00218856

Výsledek na webu

<a href="http://dx.doi.org/10.1117/12.2043621" target="_blank" >http://dx.doi.org/10.1117/12.2043621</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.2043621" target="_blank" >10.1117/12.2043621</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of microscopy images of Langerhans islets

Popis výsledku v původním jazyce

Evaluation of images of Langerhans islets is a crucial procedure for planning an islet transplantation, which is a promising diabetes treatment. This paper deals with segmentation of microscopy images of Langerhans islets and evaluation of islet parameters such as area, diameter, or volume (IE). For all the available images, the ground truth and the islet parameters were independently evaluated by four medical experts. We use a pixelwise linear classifier (perceptron algorithm) and SVM (support vector machine) for image segmentation. The volume is estimated based on circle or ellipse fitting to individual islets. The segmentations were compared with the corresponding ground truth. Quantitative islet parameters were also evaluated and compared with parameters given by medical experts. We can conclude that accuracy of the presented fully automatic algorithm is fully comparable with medical experts.

Název v anglickém jazyce

Classification of microscopy images of Langerhans islets

Popis výsledku anglicky

Evaluation of images of Langerhans islets is a crucial procedure for planning an islet transplantation, which is a promising diabetes treatment. This paper deals with segmentation of microscopy images of Langerhans islets and evaluation of islet parameters such as area, diameter, or volume (IE). For all the available images, the ground truth and the islet parameters were independently evaluated by four medical experts. We use a pixelwise linear classifier (perceptron algorithm) and SVM (support vector machine) for image segmentation. The volume is estimated based on circle or ellipse fitting to individual islets. The segmentations were compared with the corresponding ground truth. Quantitative islet parameters were also evaluated and compared with parameters given by medical experts. We can conclude that accuracy of the presented fully automatic algorithm is fully comparable with medical experts.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

30224 - Radiology, nuclear medicine and medical imaging

Projekt

<a href="/cs/project/GA14-10440S" target="_blank" >GA14-10440S: Automatická analýza mikroskopických snímků Langerhansových ostrůvků</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 statě ve sborníku

Medical Imaging 2014: Image Processing

ISBN

978-0-8194-9827-4

ISSN

0277-786X

e-ISSN

1996-756X

Počet stran výsledku

8

Strana od-do

"art. no. 90341S"

Název nakladatele

SPIE

Místo vydání

Bellingham

Místo konání akce

San Diego, US

Datum konání akce

15. 2. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000338543300062