首页> 外文会议>Image Processing and Its Applications, 1999. Seventh International Conference on (Conf. Publ. No. 465) >A registration algorithm of eye fundus images using a Bayesian Hough transform
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A registration algorithm of eye fundus images using a Bayesian Hough transform

机译:贝叶斯霍夫变换的眼底图像配准算法

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Image registration is the real challenge of retinal image analysis. Temporal registration is necessary in order to follow the various steps of a disease and to measure the evolution of some lesions. This is particularly true for patients developing diabetes, the first cause of legal blindness in most occidental countries, where the number and the turnover rate of lesions such as micro-aneurysms is related to the gravity of the illness. This paper presents an algorithm for temporal registration of retinal images based on point correspondence. The algorithm has been applied to the registration of fluorescein images (obtained after a fluorescein dye injection). The vascular tree is first detected in each image and bifurcation points are labelled with surrounding vessel orientations. An angle-based invariant is then computed in order to give a probability for two points to match. Then a Bayesian Hough transform is used to sort the possible matchings with their respective likelihood. A precise affine estimate and a score are computed for most likely transformations and the best transformation is chosen.
机译:图像配准是视网膜图像分析的真正挑战。为了跟随疾病的各个步骤并测量某些病变的进展,必须进行时间配准。对于患糖尿病的患者而言尤其如此,在大多数西方国家中,糖尿病是法定失明的首位原因,在这些国家中,微动脉瘤等病变的数量和周转率与疾病的严重程度有关。本文提出了一种基于点对应的视网膜图像时间配准算法。该算法已应用于荧光素图像的配准(荧光素染料注射后获得)。首先在每个图像中检测到血管树,并用周围的血管方向标记分叉点。然后计算基于角度的不变量,以便给出两个点匹配的概率。然后,使用贝叶斯霍夫变换对可能的匹配及其各自的似然度进行排序。为最可能的变换计算精确的仿射估计和分数,并选择最佳变换。

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