Rapantzikos K, Zervakis M, Balas K
Department of Electronic Computer Engineering, Digital Image and Signal Processing Laboratory, Technical University of Crete, GR-73100 Crete, Greece.
Med Image Anal. 2003 Mar;7(1):95-108. doi: 10.1016/s1361-8415(02)00093-2.
Assessment of the risk for the development of age-related macular degeneration requires reliable detection and quantitative mapping of retinal abnormalities that are considered as precursors of the disease. Typical signs for the latter are the so-called drusen that appear as abnormal white-yellow deposits on the retina. Segmentation of these features using conventional image analysis methods is quite complicated mainly due to the non-uniform illumination and the variability of the pigmentation of the background tissue. This paper presents a novel segmentation algorithm for the automatic detection and mapping of drusen in retina images acquired with the aid of a digital Fundus camera. We employ a modified adaptive histogram equalization, namely the multilevel histogram equalization (MLE) scheme, for enhancing local intensity structures. For the detection of drusen in retina images, we develop a novel segmentation technique, the histogram-based adaptive local thresholding (HALT), which extracts the useful information from an image without being affected by the presence of other structures. We provide experimental results from the application of our technique to real images, where certain abnormalities (drusen) have slightly different characteristics from the background. The performance of the algorithm is established through statistical analysis of the results. This analysis indicates that the proposed drusen detector gives reliable detection accuracy in both position and mass size.
评估年龄相关性黄斑变性的发病风险需要对被视为该疾病先兆的视网膜异常进行可靠检测和定量映射。后者的典型体征是所谓的玻璃膜疣，表现为视网膜上异常的白黄色沉积物。使用传统图像分析方法对这些特征进行分割相当复杂，主要原因是光照不均匀以及背景组织色素沉着的变异性。本文提出了一种新颖的分割算法，用于在借助数字眼底相机获取的视网膜图像中自动检测和映射玻璃膜疣。我们采用一种改进的自适应直方图均衡化方法，即多级直方图均衡化（MLE）方案，来增强局部强度结构。为了在视网膜图像中检测玻璃膜疣，我们开发了一种新颖的分割技术，即基于直方图的自适应局部阈值化（HALT），该技术可从图像中提取有用信息，而不受其他结构存在的影响。我们提供了将我们的技术应用于真实图像的实验结果，其中某些异常（玻璃膜疣）与背景的特征略有不同。通过对结果的统计分析确定了算法的性能。该分析表明，所提出的玻璃膜疣检测器在位置和质量大小方面都给出了可靠的检测精度。
