[Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
; 34(6): 869-875, 2017 Jun 01.
Article
em Zh
| MEDLINE
| ID: mdl-29761981
ABSTRACT
In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K-means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Clinical_trials
/
Guideline
/
Prognostic_studies
Idioma:
Zh
Revista:
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Assunto da revista:
ENGENHARIA BIOMEDICA
Ano de publicação:
2017
Tipo de documento:
Article