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首页> 外文期刊>Journal of Medical Engineering >Extraction of Blood Vessels in Retinal Images Using Four Different Techniques
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Extraction of Blood Vessels in Retinal Images Using Four Different Techniques

机译:使用四种不同技术提取视网膜图像中的血管

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A variety of blood vessel extraction (BVE) techniques exist in the literature, but they do not always lead to acceptable solutions especially in the presence of anomalies where the reported work is limited. Four techniques are presented for BVE: (1) BVE using Image Line Cross-Sections (ILCS), (2) BVE using Edge Enhancement and Edge Detection (EEED), (3) BVE using Modified Matched Filtering (MMF), and (4) BVE using Continuation Algorithm (CA). These four techniques have been designed especially for abnormal retinal images containing low vessel contrasts, drusen, exudates, and other artifacts. The four techniques were applied to 30 abnormal retinal images, and the success rate was found to be (95 to 99%) for CA, (88–91%) for EEED, (80–85%) for MMF, and (74–78%) for ILCS. Application of these four techniques to 105 normal retinal images gave improved results: (99-100%) for CA, (96–98%) for EEED, (94-95%) for MMF, and (88–93%) for ILCS. Investigations revealed that the four techniques in the order of increasing performance could be arranged as ILCS, MMF, EEED, and CA. Here we demonstrate these four techniques for abnormal retinal images only. ILCS, EEED, and CA are novel additions whereas MMF is an improved and modified version of an existing matched filtering technique. CA is a promising technique.
机译:文献中存在多种血管提取(BVE)技术,但是它们并不总是能导致可接受的解决方案,尤其是在存在报告的工作受限的异常情况下。针对BVE提出了四种技术:(1)使用图像线横截面(ILCS)的BVE,(2)使用边缘增强和边缘检测(EEED)的BVE,(3)使用改进的匹配滤波(MMF)的BVE,以及(4) )使用连续算法(CA)的BVE。这四种技术是专为包含低血管对比度,玻璃疣,渗出液和其他伪影的异常视网膜图像而设计的。四种技术均应用于30幅异常视网膜图像,发现CA的成功率为(95%至99%),EEED的成功率为(88-91%),MMF的成功率为(80-85%),而(74- 78%)。将这四种技术应用于105个正常视网膜图像可得到更好的结果:CA(99-100%),EEED(96–98%),MMF(94-95%)和ILCS(88–93%) 。调查显示,可以将四种技术按性能提高的顺序排列为ILCS,MMF,EEED和CA。在这里,我们仅针对异常的视网膜图像演示这四种技术。 ILCS,EEED和CA是新增功能,而MMF是现有匹配过滤技术的改进和改进版本。 CA是一种很有前途的技术。

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