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Iterative h-minima-based marker-controlled watershed for cell nucleus segmentation.
Koyuncu, Can Fahrettin; Akhan, Ece; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem.
Afiliação
  • Koyuncu CF; Computer Engineering Department, Bilkent University, Ankara, TR-06800, Turkey.
  • Akhan E; Molecular Biology and Genetics Department, Bilkent University, Ankara, TR-06800, Turkey.
  • Ersahin T; Medical Informatics Department, Graduate School of Informatics, Middle East Technical University, Ankara, TR-06800, Turkey.
  • Cetin-Atalay R; Medical Informatics Department, Graduate School of Informatics, Middle East Technical University, Ankara, TR-06800, Turkey.
  • Gunduz-Demir C; Computer Engineering Department, Bilkent University, Ankara, TR-06800, Turkey.
Cytometry A ; 89(4): 338-49, 2016 04.
Article em En | MEDLINE | ID: mdl-26945784
ABSTRACT
Automated microscopy imaging systems facilitate high-throughput screening in molecular cellular biology research. The first step of these systems is cell nucleus segmentation, which has a great impact on the success of the overall system. The marker-controlled watershed is a technique commonly used by the previous studies for nucleus segmentation. These studies define their markers finding regional minima on the intensity/gradient and/or distance transform maps. They typically use the h-minima transform beforehand to suppress noise on these maps. The selection of the h value is critical; unnecessarily small values do not sufficiently suppress the noise, resulting in false and oversegmented markers, and unnecessarily large ones suppress too many pixels, causing missing and undersegmented markers. Because cell nuclei show different characteristics within an image, the same h value may not work to define correct markers for all the nuclei. To address this issue, in this work, we propose a new watershed algorithm that iteratively identifies its markers, considering a set of different h values. In each iteration, the proposed algorithm defines a set of candidates using a particular h value and selects the markers from those candidates provided that they fulfill the size requirement. Working with widefield fluorescence microscopy images, our experiments reveal that the use of multiple h values in our iterative algorithm leads to better segmentation results, compared to its counterparts. © 2016 International Society for Advancement of Cytometry.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Reconhecimento Automatizado de Padrão / Aumento da Imagem / Biomarcadores / Núcleo Celular Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cytometry A Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Turquia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Reconhecimento Automatizado de Padrão / Aumento da Imagem / Biomarcadores / Núcleo Celular Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cytometry A Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Turquia