DESIGN AND DEVELOPMENT OF A DESIGN TOOL FOR ENHANCED FLUORESCEIN ANGIOGRAPHY

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 静脉荧光素血管造影术(IVFA)是一种公认的诊断工具，它有助于规划眼科疾病(如新生血管性老年性黄斑变性、糖尿病视网膜病变和其他疾病)的激光治疗。该技术是眼科提供的所有视网膜相关服务所需的标准诊断工具。IVFA生成一系列视网膜循环的单帧、彩色过滤、单色图像，其中每一帧都以单独的35 mm幻灯片或数字图像的形式存储。我们提出了一种新的计算框架，它具有交互式图形用户界面(GUI)，将一系列经过处理的单色IVFA图像呈现为动画。由于非自主快速眼球运动、不同角度的成像和晶状体变形引起的跨序列不一致，图像应该被配准，以便为IVFA操作提供尽可能好的诊断。 这一过程包括四个主要的计算步骤：a)图像增强，即识别渗出物和视盘，并用平均强度像素值取代渗出物和视盘，以消除虚假警报。然后执行平滑以去除噪声，随后执行对比度增强以帮助锐化血管以进行视觉检查；b)基于刚体变换执行图像配准。对旋转和平移的补偿是以亚像素精度实现的；c)通过在配准图像上添加信息性假颜色以发现和解释视网膜图像中感兴趣的特征，进一步加强了这一过程。标签被分配给图像中连接的对象，然后以矩阵的形式收集。然后将矩阵转换为RGB彩色图像以便于可视化；d)图形用户界面(GUI)将以统一的动画格式提供算法结果的自主视图。开发的计算框架通过提供更好的视网膜循环及其生理模型，提供了更容易查看和推断功能性血管缺陷的方法。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Intravenous Fluorescein Angiography (IVFA) is a well-established diagnostic tool which assists in planning laser treatments for ophthalmological disorders (e.g., neovascular age- related macular degeneration, diabetic retinopathy, and other disorders). The technology is a standard diagnostic tool required for all retina-related services offered by ophthalmology departments. IVFA produces a series of single frame, color filtered, monochrome views of the retinal circulation, where each individual frame is stored as a separate 35 mm slide or digital image. We present a novel computational framework with an interactive Graphical User Interface (GUI) that presents the series of processed, monochrome IVFA images as an animation. Due to cross-series inconsistencies caused by involuntary rapid eye movements, imaging from different angles, and lens distortion, the images should be registered in order to provide the best possible diagnosis of the IVFA procedure. The process involves four major computational step: a) image enhancement which identifies and replaces exudates and optic discs by average intensity pixel values in order to dismiss false alarms. Smoothening is then performed for noise removal, followed by contrast enhancement which aids in the sharpening of blood vessels for visual inspection; b) image registration is performed based on rigid body transforms. Compensation for rotation and translation is achieved with sub-pixel accuracy; c) the process is further reinforced by adding an informative false color to the registered image for discovery and interpretation of features of interest within retinal images. Labels are assigned to the connected objects in the image and then collected in the form of a matrix. The matrix is then converted into an RGB color image for ease of visualization; d) Graphical User Interface (GUI) will provide an autonomous view of the algorithmic results in an unified animated format. The developed computational framework provides easier viewing and inference of functional vascular defects by providing better models of retinal circulation and its physiology.