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Automated Quantification of Macular Vasculature Changes from OCTA Images of Hematologic Patients

机译:从血液学患者的OCTA图像中自动定量黄斑脉管变化

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Abnormal blood compositions can lead to abnormal blood flow which can influence the macular vasculature. Optical coherence tomography angiography (OCTA) makes it possible to study the macular vasculature and potential vascular abnormalities induced by hematological disorders. Here, we investigate vascular changes in control subjects and in hematologic patients before and after treatment. Since these changes are small, they are difficult to notice in the OCTA images. To quantify vascular changes, we propose a method for combined capillary registration, dictionary-based segmentation and local density estimation. Using this method, we investigate three patients and five controls, and our results show that we can detect small changes in the vasculature in patients with large changes in blood composition.
机译:异常的血液成分会导致异常的血流,从而影响黄斑部的脉管系统。光学相干断层扫描血管造影(OCTA)使得研究血液系统疾病引起的黄斑脉管系统和潜在的血管异常成为可能。在这里,我们调查了治疗前后对照对象和血液病患者的血管变化。由于这些变化很小,因此很难在OCTA图像中注意到它们。为了量化血管变化,我们提出了一种结合毛细血管定位,基于字典的分割和局部密度估计的方法。使用这种方法,我们调查了三名患者和五名对照,我们的结果表明,我们可以检测到血液成分变化较大的患者的脉管系统的微小变化。

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