Real-Time Algorithms for Automatic Vasculature Map Generation and Feature-Based Location Determination From Intra-Ocular Image Sequences

激光眼科手术是目前已知最有效的治疗脉络膜新生血管(CNV)的手术，可发现多种情况下的脉络膜新生血管(CNV)，包括老年性黄斑变性、组织性脉络膜炎等。然而，目前这种手术在一次治疗后根除CNV的成功率不到50%，复发率和/或持续率约为50%。这项研究将使一种可以大幅降低失败率的仪器成为可能。该仪器由一个计算机化的多光谱三维眼底相机、一个相关的平视显示器和一个实时激光跟踪系统组成。跟踪系统使用一套自动图像分析程序，允许准确绘制病理图，并进行计算机化的激光治疗计划。正在解决的核心图像处理问题是：(I)从图像序列构建视网膜血管的广域图；以及(Ii)确定当前帧相对于在步骤(I)中构建的广域图的位置，以2像素的精度，或者更好地，以至少每秒30的帧速率。上述问题正在通过开发一种快速算法来解决，该算法用于在存在少量噪声点的情况下匹配具有未知对应关系的点集。该算法通过将搜索限制到最可靠的图像特征点的最小充分性子集来操作。此外，所提出的算法正在处理器的线性阵列上实现，进一步实现了实时操作。

Laser eye surgery is the most effective known procedure for treating choroidal neovascularization (CNV) found in a variety of conditions including age-related macular degeneration, histoplasmic choroiditis, etc. However, the current rate of success of this procedure is less than 50% for eradication of the CNV following one treatment session, with a recurrence and/or persistence rate of about 50%. This research will make possible an instrument that will drastically reduce this failure rate. The instrument consists of a computerized multi-spectral 3-D fundus camera with an associated head-up display and a real-time laser tracking system. The tracking system uses a set of automatic image analysis routines that allow accurate mapping of the pathologies, and computerized laser treatment planning. The core image-processing problems that are being addressed are: (i) constructing a wide-area map of the retinal vasculature from an image sequence; and (ii) determining the location of the current frame relative to the wide-area map constructed in step (i) to an accuracy of 2 pixels, or better, at a frame rate of at least 30 per second. The above problems are being solved by the development of a fast algorithm for matching point sets with unknown correspondences, in the presence of a small number of noise points. This algorithm operates by limiting the search to a minimally- sufficient subset of the most reliable image feature points. In addition, the proposed algorithm is being implemented on a linear array of processors, further enabling real-time operation.