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首页> 外文期刊>Computer methods in biomechanics and biomedical engineering >Automatic detection of age-related macular degeneration pathologies in retinal fundus images
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Automatic detection of age-related macular degeneration pathologies in retinal fundus images

机译:自动检测视网膜眼底图像中与年龄相关的黄斑变性病变

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摘要

Advanced techniques in image processing and analysis are being extensively studied to assist clinical diagnoses. Digital colour retinal fundus images are widely utilised to investigate various eye diseases. In this paper, we describe the detection of optic disc (OD), macula and age-related macular degeneration (ARMD) pathologies of the macular regions in colour fundus images. ARMD causes the loss of central vision in older adults. If the disease is detected early and treated promptly, much of the vision loss can be prevented. Eighty colour retinal fundus images were tested using our proposed algorithm. The Hough transform was employed for OD determination. A fundus coordinate system was established based on the macula location. An ARMD pathology detection methodology using a subtraction process after contrast-limited adaptive histogram equalisation operations was proposed. The accuracies of the automated segmentations of the OD, macula and ARMD pathologies obtained were 100%, 100% and 95.49%, respectively. These results show that our algorithm is a useful tool for detecting ARMD in retinal fundus images. The application of our method may reduce the time needed by ophthalmologists to diagnose ARMD pathology while providing dependable detection precision. Integration of our technique into traditional software could be used in clinical implementations as an aid in disease diagnosis and as a tool for quantitative evaluation of treatment effectiveness.
机译:图像处理和分析中的先进技术正在广泛研究中,以协助临床诊断。数字彩色视网膜眼底图像被广泛用于研究各种眼部疾病。在本文中,我们描述了彩色眼底图像中黄斑区域的视盘(OD),黄斑和年龄相关性黄斑变性(ARMD)病理的检测。 ARMD会导致老年人失去中央视力。如果及早发现疾病并及时治疗,则可以预防很多视力丧失。使用我们提出的算法测试了80个彩色视网膜眼底图像。霍夫变换用于OD测定。根据黄斑位置建立眼底坐标系。提出了一种在对比度受限的自适应直方图均衡操作后使用减法处理的ARMD病理学检测方法。获得的OD,黄斑和ARMD病理学自动分割的准确性分别为100%,100%和95.49%。这些结果表明,我们的算法是检测视网膜眼底图像中ARMD的有用工具。我们方法的应用可以减少眼科医生诊断ARMD病理所需的时间,同时提供可靠的检测精度。我们的技术与传统软件的集成可用于临床实施,以帮助疾病诊断和定量评估治疗效果。

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