Automatic Biological Cell Counting Using a Modified Gradient Hough Transform.
Microsc Microanal
; 23(1): 11-21, 2017 02.
Article
em En
| MEDLINE
| ID: mdl-28143631
ABSTRACT
We present a computational method for pseudo-circular object detection and quantitative characterization in digital images, using the gradient accumulation matrix as a basic tool. This Gradient Accumulation Transform (GAT) was first introduced in 1992 by Kierkegaard and recently used by Kaytanli & Valentine. In the present article, we modify the approach by using the phase coding studied by Cicconet, and by adding a "local contributor list" (LCL) as well as a "used contributor matrix" (UCM), which allow for accurate peak detection and exploitation. These changes help make the GAT algorithm a robust and precise method to automatically detect pseudo-circular objects in a microscopic image. We then present an application of the method to cell counting in microbiological images.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Reconhecimento Automatizado de Padrão
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Técnicas Microbiológicas
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Microscopia
Idioma:
En
Revista:
Microsc Microanal
Ano de publicação:
2017
Tipo de documento:
Article