Chrástek R, Skokan M, Kubecka L, Wolf M, Donath K, Jan J, Michelson G, Niemann H
Chair for Pattern Recognition, Friedrich-Alexander-University, Erlangen, Germany.
Methods Inf Med. 2004;43(4):336-42.
The analysis of the optic disk morphology with the means of the scanning laser tomography is an important step for glaucoma diagnosis. A method we developed for optic disk segmentation in images of the scanning laser tomograph is limited by noise, non-uniform illumination and presence of blood vessels. Inspired by recent medical research, we wanted to develop a tool for improving optic disk segmentation by registration of images of the scanning laser tomograph and color fundus photographs and by applying a method we developed for optic disk segmentation in color fundus photographs.
The segmentation of the optic disk for glaucoma diagnosis in images of the scanning laser tomograph is based on morphological operations, detection of anatomical structures and active contours and has been described in a previous paper. The segmentation of the optic disk in the fundus photographs is based on nonlinear filtering, Canny edge detector and a modified Hough transform. The registration is based on mutual information using simulated annealing for finding maxima.
The registration was successful 86.8% of the time when tested on 174 images. Results of the registration have shown a very low displacement error of a maximum of about 5 pixels. The correctness of the registration was manually evaluated by measuring distances between the real vessel borders and those from the registered image.
We have developed a method for the registration of images of the scanning laser tomograph and fundus photographs. Our first experiments showed that the optic disk segmentation could be improved by fused information from both image modalities.
利用扫描激光断层扫描技术分析视盘形态是青光眼诊断的重要步骤。我们开发的一种用于扫描激光断层扫描图像中视盘分割的方法受到噪声、光照不均匀和血管存在的限制。受近期医学研究的启发,我们希望开发一种工具,通过对扫描激光断层扫描图像和彩色眼底照片进行配准,并应用我们开发的一种用于彩色眼底照片中视盘分割的方法,来改进视盘分割。
扫描激光断层扫描图像中用于青光眼诊断的视盘分割基于形态学操作、解剖结构检测和活动轮廓,前文已有描述。眼底照片中视盘的分割基于非线性滤波、Canny边缘检测器和改进的霍夫变换。配准基于互信息,使用模拟退火算法寻找最大值。
在174幅图像上进行测试时,配准成功率为86.8%。配准结果显示最大位移误差非常低,最多约5个像素。通过测量真实血管边界与配准图像中血管边界之间的距离,人工评估配准的正确性。
我们开发了一种扫描激光断层扫描图像与眼底照片的配准方法。我们的初步实验表明,通过融合两种图像模态的信息可以改进视盘分割。