Kamasi Zeinab Ghasemi, Mokhtari Marzieh, Rabbani Hossein
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:4415-4418. doi: 10.1109/EMBC.2017.8037835.
Fluorescein Angiography (FA) imaging is the gold standard technique for neurovascular imaging regarding assessing neurovascular diseases such as Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME). On the other hand, as FA imaging is invasive and does not provide any depth information, Optical Coherence Tomography (OCT) imaging technique is a good complementary for it in diagnosis process. To correlate the information of both FA and OCT images, an image alignment/registration process is needed. In absence of an automatic registration software, the clinician should do intuitive comparison to integrate these data which is a subjective and time consuming process. In this paper, we demonstrate a non-rigid registration method called multi-step correlation-based registration algorithm to automatically register FA and OCT images together. Our algorithm consists of two steps including rigid/global and non-rigid/local registration. We evaluate our algorithm's performance by labeling Micro-Aneurysm (MA) spots -hallmarks of DR- on FA images and determining MA regions on OCT B-scans after registration. Our Results show that our algorithm performs accurately regarding registration of FA images and OCT B-scans.
荧光素血管造影(FA)成像在评估糖尿病视网膜病变(DR)和糖尿病性黄斑水肿(DME)等神经血管疾病方面,是神经血管成像的金标准技术。另一方面,由于FA成像具有侵入性且不提供任何深度信息,光学相干断层扫描(OCT)成像技术在诊断过程中是其良好的补充。为了关联FA和OCT图像的信息,需要进行图像对齐/配准过程。在没有自动配准软件的情况下,临床医生应进行直观比较以整合这些数据,这是一个主观且耗时的过程。在本文中,我们展示了一种称为基于多步相关性的配准算法的非刚性配准方法,用于自动将FA和OCT图像配准在一起。我们的算法包括刚性/全局和非刚性/局部配准两个步骤。我们通过在FA图像上标记微动脉瘤(MA)斑点(DR的标志)并在配准后确定OCT B扫描上的MA区域来评估我们算法的性能。我们的结果表明,我们的算法在FA图像和OCT B扫描的配准方面表现准确。