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Automation of the Detection of Pathological Changes in the Morphometric Characteristics of the Human Eye Fundus Based on the Data of Optical Coherence Tomography Angiography

机译:基于光学相干断层造影造影的数据的人眼基底形态测量特征的检测自动化

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This paper presents the results of the joint work of image analysis specialists and ophthalmologists on the task of analyzing images obtained by the method of optical coherence tomography angiography. A method was developed to automate the detection of pathological changes in the morphometric characteristics of the fundus. The solution of the image recognition problem assumes the presence of certain image representations, the presence of effective recognition algorithms, and the compliance of the used image representations with the requirements of the recognition algorithms for the source data. To reduce images to a form that is easy to recognize we considered sets of features that met all the necessary requirements of specialists. Chosen feature model was implemented to the problem of classification of images of patients with and without pathologies. The developed method makes it possible to classify pathological changes in the vascular bed of the human eye with high accuracy.
机译:本文介绍了图像分析专家和眼科医生联合作品的结果,以分析通过光学相干断层造影血管造影方法获得的图像的任务。 开发了一种方法,以自动检测眼底的形态学特性的病理变化。 图像识别问题的解决方案假定存在某些图像表示,存在有效识别算法的存在,以及所使用的图像表示与用于源数据的识别算法的要求的顺应性。 将图像缩短到易于识别的形式,我们认为我们认为一组特征符合专家所需的所有要求。 选择特征模型是对患者的分类问题,无病理学的分类问题。 开发的方法使得可以以高精度对人眼的血管床进行分类病理变化。

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