[Overlapping Cervical Cell Image Segmentation Based on Bottleneck Detection and Watershed Algorithm].
Zhongguo Yi Liao Qi Xie Za Zhi
; 44(1): 7-12, 2020 Jan 08.
Article
em Zh
| MEDLINE
| ID: mdl-32343058
ABSTRACT
This study proposes an image segmentation method based on bottleneck detection and watershed algorithm to solve the problem of overlapping cervical cell image. First, we use polygon approximation to get all feature points on the cell contour and then use bottleneck detection and ellipse fitting to obtain the correct split point pairs. Therefore, the approximate range of the overlapping region was determined. The watershed algorithm was used to obtain the internal boundary information for the gradient image of the region. Finally, the segmentation results of the overlapped cells were obtained by superimposing with the outer contour. The experimental results show that this algorithm can segment the contour of a single cell from the overlapping cervical cell images with good accuracy and integrity. The segmentation result is close to that of doctors' manual marking, and the segmentation result is better than other existing algorithms.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Processamento de Imagem Assistida por Computador
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Colo do Útero
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Female
/
Humans
Idioma:
Zh
Ano de publicação:
2020
Tipo de documento:
Article