A Comparison of Fast Level Set-like Algorithms for Image Segmentation in Fluorescence Microscopy

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F07%3A00022769" target="_blank" >RIV/00216224:14330/07:00022769 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

A Comparison of Fast Level Set-like Algorithms for Image Segmentation in Fluorescence Microscopy

Original language description

Image segmentation, one of the fundamental task of image processing, can be accurately solved using the level set framework. However, the computational time demands of the level set methods make them practically useless, especially for segmentation of large threedimensional images. Many approximations have been introduced in recent years to speed up the computation of the level set methods. Although these algorithms provide favourable results, most of them were not properly tested against ground truth images. In this paper we present a comparison of three methods: the Sparse-Field method [1], Deng and Tsui's algorithm [2] and Nilsson and Heyden's algorithm [3]. Our main motivation was to compare these methods on 3D image data acquired using fluorescence microscope, but we suppose that presented results are also valid and applicable to other biomedical images like CT scans, MRI or ultrasound images. We focus on a comparison of the method accuracy, speed and ability to detect several obj

Czech name

Porovnání rychlých aproximací Level Set metody pro segmentaci obrazu ve fluorescenční mikroskopii

Czech description

Segmentaci obrazu, jednu ze základních úloh zpracování obrazu, lze přesně řešit pomocí Level Set metody.

Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2007

Confidentiality

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

Article name in the collection

Advances in Visual Computing

ISBN

978-3-540-76855-5

ISSN

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e-ISSN

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Number of pages

11

Pages from-to

571-581

Publisher name

Spinger-Verlag

Place of publication

Berlin, Heidelberg

Event location

Lake Tahoe, Nevada/California

Event date

Nov 26, 2007

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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