Two-Steps Coronary Artery Segmentation Algorithm Based on Improved Level Set Model in Combination with Weighted Shape-Prior Constraints.

Due to the complex topological structure of the coronary artery and the uneven distribution of the contrast agent, the angiography images are inevitably blurred and has low contrast, which causes great difficulty in process of segmentation. For this problem, a two-steps segmentation algorithm based...

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Publicado en:Journal of Medical Systems Vol. 43; no. 7
Autores principales: Ge, Shang, Shi, Zhaofei, Peng, Guangming, Zhu, Zhaohuan
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Jul2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2019
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      pub: Springer Nature
      place: New York, New York
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        atl: Two-Steps Coronary Artery Segmentation Algorithm Based on Improved Level Set Model in Combination with Weighted Shape-Prior Constraints.
      aug:
        au:
          Ge, Shang
          Shi, Zhaofei
          Peng, Guangming
          Zhu, Zhaohuan
        affil: Department of Radiology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, 223300, Huaian, Jiangsu, China
      sug:
        subj:
          Coronary Vessels Pathology
          Coronary Angiography
          Algorithms Methods
          Human
          Diagnosis, Computer Assisted
          Mathematics
          Coronary Disease Diagnosis
          Qualitative Studies
          Quantitative Studies
      ab: Due to the complex topological structure of the coronary artery and the uneven distribution of the contrast agent, the angiography images are inevitably blurred and has low contrast, which causes great difficulty in process of segmentation. For this problem, a two-steps segmentation algorithm based on Hessian matrix and level set is proposed in this paper. Firstly, potential blood vessels of coronary images are preliminary extracted via Hessian matrix eigenvalues feature vectors of the geometric features and the response function. Then a novel regularization and area constraint is introduced into the local data energy fitting functional. Finally, the precision of Coronary Artery image is obtained in the evolution of the level set function. Experiments show that our proposed algorithm has better performance to these comparison segmentation algorithms.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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