Future Convergenc e Engineering, Korea University of Technology and Education, 1600, Chungjeolro, Byeongcheonmyeon, 31253 Cheonan, Republic of Korea.
School of of Mechatronics Engineering, Tech Universith of Korea, 237 Sangidaehak-ro, Siheung-si, Gyeonggi-do 15073, Republic of Korea; IKLAB Inc., 237 Sangidaehak-ro, Siheung-si, Gyeonggi-do 15073, Republic of Korea.
Comput Med Imaging Graph. 2022 Jun;98:102058. doi: 10.1016/j.compmedimag.2022.102058. Epub 2022 Mar 28.
Optic disc localization, a key preprocessing step in the analysis of color fundus images for diagnoses of eye diseases and the localization of various anatomical structures, is particularly challenging when input retina images contain abnormalities. In such cases, the disc can be confused with other anatomical structures such as fovea, exudates, vessel tree extraction, and retinopathy-related lesions. Herein, we present a method for effective optic disc detection and localization based on color and blur analysis. In this method, the input color fundus image is converted to CIE Lab* color space to enhance optic disc appearance and contrast, and the accumulated directional blur and extended-maxima transform are then applied to precisely extract optic disc candidates. Subsequently, radial blur is applied to each candidate to obtain better profiles and thus distinguish the optic disc from other candidates. Finally, the full width at 80% maximum (FW80M) metric is used to select the optic disc. The performance of the proposed method is evaluated using well-studied data sets, and comparison of the obtained results with those of state-of-the-art techniques reveals the effectiveness of our method and shows that it can precisely locate the disc position not only in normal cases but also in the presence of exudates and abnormalities.
视盘定位是分析眼底彩色图像以诊断眼部疾病和定位各种解剖结构的关键预处理步骤,当输入的视网膜图像包含异常时,该步骤尤其具有挑战性。在这种情况下,视盘可能会与其他解剖结构(如黄斑、渗出物、血管树提取和与视网膜病变相关的病变)混淆。在此,我们提出了一种基于颜色和模糊分析的有效视盘检测和定位方法。在该方法中,将输入的眼底彩色图像转换为 CIE Lab*颜色空间,以增强视盘的外观和对比度,然后应用累积方向模糊和扩展极大值变换,以精确提取视盘候选区域。随后,对每个候选区域应用径向模糊,以获得更好的轮廓,从而将视盘与其他候选区域区分开来。最后,使用 80%最大全宽(FW80M)度量标准选择视盘。使用经过充分研究的数据集评估所提出方法的性能,将获得的结果与最先进技术的结果进行比较,表明该方法不仅可以在正常情况下,而且可以在存在渗出物和异常的情况下精确定位视盘位置,具有有效性。