Object

Title: Novel statistical approach for segmentation of brain magnetic resonance imaging using an improved expectation maximization algorithm

Creator:

Yang, Yong ; Huang, Shuying

Contributor:

Gaj, Miron. Redakcja ; Wilk, Ireneusz. Redakcja

Description:

Optica Applicata, Vol. 36, 2006, nr 1, s. 125-136

Abstrakt:

In this paper, an improved expectation maximization (EM) algorithm called statistical histogram based expectation maximization (SHEM) algorithm is presented. The algorithm is put forward to overcome the drawback of standard EM algorithm, which is extremely computationally expensive for calculating the maximum likelihood (ML) parameters in the statistical segmentation. Combining the SHEM algorithm and the connected threshold region-growing algorithm that is used to provide a priori knowledge, a novel statistical approach for segmentation of brain magnetic resonance (MR) image data is thus proposed. The performance of our SHEM based method is compared with those of the EM based method and the commonly applied fuzzy C-means (FCM) segmentation. Experimental results show the proposed approach to be effective, robust and significantly faster than the conventional EM based method.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2006

Resource Type:

artykuł

Resource Identifier:

oai:dbc.wroc.pl:63422

Source:

<sygn. PWr A3481II> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Optica Applicata ; Optica Applicata, Vol. 36, 2006 ; Optica Applicata, Vol. 36, 2006, nr 1 ; Politechnika Wrocławska. Wydział Podstawowych Problemów Techniki

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska

Group publication title:

Optica Applicata

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