计算机上静脉串珠平行分级

Tien-You Lee, H.D. Cheng
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引用次数: 2

摘要

描述了一种用于数字化眼底图像中静脉串珠自动分级的并行算法及其在转盘上的实现。该算法主要包括中值滤波、阈值分割、细化、形态闭合、直径测量、快速傅里叶变换(FFT)分析和分级。中值滤波降低原始图像中的噪声,阈值分割从背景中粗略提取静脉,形态学闭合填充静脉中的孔洞,细化得到静脉的中心线表示,对每个中心线分支进行直径测量和分析,FFT对直径函数进行分析。计算了直径函数的幅度谱。通常没有串珠的脉体只有低频成分,而串珠脉体有更多的高频成分。高频幅值的总和可以作为区分正常脉和串珠脉的参数。所有的工作都是在一台使用PC Trollius的计算机上完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel grading of venous beading on transputer
Describes a parallel algorithm and its implementation on transputers for automated grading of venous beading in digitized ocular fundus images. The algorithm mainly consists of median filtering, thresholding, thinning, morphological closing, diameter measurement, fast Fourier transform (FFT) analysis and grading. Median filtering reduces the noise in the original image, thresholding roughly extracts the vein from the background, morphological closing fills holes in the vein, thinning obtains a centerline representation of the vein, diameter measurement and analysis are performed on each centerline branch, and the FFT analyzes the diameter functions. The magnitude spectrum of the diameter function is computed. Usually veins without beading exhibit only low frequency components while beaded veins have significantly more high frequency components. The sum of the high frequency magnitude can be a parameter to distinguish normal from beaded veins. All work has been done on a transputer using PC Trollius.<>
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