Zhou X, Shi P, Zhang C
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2000 Jun;17(2):170-3.
Object description in medical image often has the property of fuzziness, and with the development of computing, fuzzy logical theories are progressively used in medical image processing. Color medical images differ in spacial presentation and fuzzy description from grey-scale images and must be analyzed by special methods. In this paper, a new method of bone cell segmentation based on fuzzy logical theories is presented. With the utilization of fuzzy set theories in the steps of color enhancing, feature extraction and automatical segmentation, bone cells are detected from the background. The method has the advantages of high accuracy and flexibility to many situations. Experiments of bone cell images have proved that it is a fast and effective method.
医学图像中的目标描述通常具有模糊性,随着计算技术的发展,模糊逻辑理论逐渐应用于医学图像处理中。彩色医学图像在空间表现和模糊描述方面与灰度图像不同,必须采用特殊方法进行分析。本文提出了一种基于模糊逻辑理论的骨细胞分割新方法。通过在颜色增强、特征提取和自动分割步骤中运用模糊集理论,从背景中检测出骨细胞。该方法具有精度高、对多种情况适应性强的优点。骨细胞图像实验证明,它是一种快速有效的方法。