Retinal vessel optical coherence tomography images for anemia screening.

Anemia is a disease that leads to low oxygen carrying capacity in the blood. Early detection of anemia is critical for the diagnosis and treatment of blood diseases. We find that retinal vessel optical coherence tomography (OCT) images of patients with anemia have abnormal performance because the in...

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Publicado en:Medical & Biological Engineering & Computing Vol. 56; no. 12
Autores principales: Chen, Zailiang, Mo, Yufang, Ouyang, Pingbo, Shen, Hailan, Li, Dabao, Zhao, Rongchang
Formato: Journal Article
Publicado: Springer Nature Dec2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2018
      vid: 56
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-018-1927-8
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      aug:
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          Chen, Zailiang
          Mo, Yufang
          Ouyang, Pingbo
          Shen, Hailan
          Li, Dabao
          Zhao, Rongchang
        affil: School of Information Science and Engineering, Central South University, Changsha, 410083, China
      sug:
        subj:
          Anemia Diagnosis
          Tomography, Optical Coherence
          Retina
          Health Screening
          Image Interpretation, Computer Assisted
          Data Mining
          Algorithms
          Factor Analysis
          Scales
      ab: Anemia is a disease that leads to low oxygen carrying capacity in the blood. Early detection of anemia is critical for the diagnosis and treatment of blood diseases. We find that retinal vessel optical coherence tomography (OCT) images of patients with anemia have abnormal performance because the internal material of the vessel absorbs light. In this study, an automatic anemia screening method based on retinal vessel OCT images is proposed. The method consists of seven steps, namely, denoising, region of interest (ROI) extraction, layer segmentation, vessel segmentation, feature extraction, feature dimensionality reduction, and classification. We propose gradient and threshold algorithm for ROI extraction and improve region growing algorithm based on adaptive seed point for vessel segmentation. We also conduct a statistical analysis of the correlation between hemoglobin concentration and intravascular brightness and vascular shadow in OCT images before feature extraction. Eighteen statistical features and 118 texture features are extracted for classification. This study is the first to use retinal vessel OCT images for anemia screening. Experimental results demonstrate the accuracy of the proposed method is 0.8358, which indicates that the method has clinical potential for anemia screening. Graphical abstract.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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