IEEE J Biomed Health Inform. 2018 Mar;22(2):570-578. doi: 10.1109/JBHI.2017.2652446. Epub 2017 Jan 13.
Indocyanine green (ICG) angiography is an imaging method for doctors to observe choroidal abnormalities in human eyes. The ICG angiograms typically exhibit inhomogeneous illumination, which poses serious difficulties for the development of computer-aided diagnostic tools. In this paper, we propose a novel illumination normalization method to alleviate the inhomogeneous illumination in ICG video angiograms. In particular, we first align the viewpoint of the input ICG video angiogram using an image registration method. Then, we acquire temporal information using time-dependent intrinsic image and compute the corresponding illumination image. Finally, we correct inhomogeneous illumination from the illumination image by estimating contrast and luminosity distortion. We have conducted extensive evaluation using ICG video angiograms of 60 patients. Two video quality assessment methods are utilized to evaluate the performance of our proposed illumination normalization method. The results show that our proposed method can help improve the visual quality of ICG video angiogram. Visual evaluation by a human expert also confirms that our method yields better illumination normalization results.
吲哚菁绿（ICG）血管造影是一种医生观察人眼脉络膜异常的成像方法。ICG 血管造影图通常表现出不均匀的照明，这给计算机辅助诊断工具的开发带来了严重的困难。在本文中，我们提出了一种新的照明归一化方法，以减轻 ICG 视频血管造影中的不均匀照明。具体来说，我们首先使用图像配准方法对齐输入的 ICG 视频血管造影的视角。然后，我们使用时变固有图像获取时间信息，并计算相应的照明图像。最后，我们通过估计对比度和亮度失真来从照明图像中校正不均匀的照明。我们使用 60 名患者的 ICG 视频血管造影进行了广泛的评估。使用两种视频质量评估方法来评估我们提出的照明归一化方法的性能。结果表明，我们提出的方法可以帮助提高 ICG 视频血管造影的视觉质量。人类专家的视觉评估也证实了我们的方法可以产生更好的照明归一化效果。
