论文部分内容阅读
目的:寻求一种骨小梁显微图像参数自动提取的方法并将之应用于骨质疏松症中。方法:采用计算机自动识别,在通用PC平台上改进,使骨小梁间隙能够自动识别,在处理的过程中对人机对话进行了改进,使之能处理原始图像不够完善的情况。结果:骨小梁数随年龄增加而逐渐减少,表明所形成的游离骨小梁随年龄增加逐渐被清除,计算机自动提取结果同临床分析相一致。结论:与以往研究方法相比的最大优点是细化处理的效果较好,并在自动提取时增进了人机对话,使准确性和智能化上得到了显著提高。
OBJECTIVE: To find a method for the automatic extraction of trabecular bone microscopic image parameters and to apply it in osteoporosis. Methods: The automatic recognition by computer and the improvement on the common PC platform make the trabecular bone gap be recognized automatically. In the course of processing, the man-machine dialogue is improved so that the original image is not perfect enough. Results: Trabecular number decreased gradually with age, indicating that the formed free trabecular bone was gradually cleared with age. The results of automatic computer extraction were consistent with those of clinical analysis. Conclusion: Compared with the previous research methods, the biggest advantage is the fine processing effect is better, and in the automatic extraction to enhance the man-machine dialogue, the accuracy and intelligence has been significantly improved.