参数化的粘性形态学分水岭理论方法及其在医学肿瘤分割中的应用研究

项目名称： 参数化的粘性形态学分水岭理论方法及其在医学肿瘤分割中的应用研究

项目编号： No.61261029

项目类型： 地区科学基金项目

立项/批准年度： 2013

项目学科： 无线电电子学、电信技术

项目作者： 王小鹏

作者单位： 兰州交通大学

项目金额： 40万元

中文摘要： ：形态学分水岭分割能够产生封闭且定位准确的图像目标区域轮廓，适合于医学肿瘤的分割需求，但存在过分割现象，对原始图像进行平滑滤波可以减轻或消除过分割，但容易使分割后的区域轮廓发生位置偏移。为此项目拟采用粘性流体替代经典分水岭中的水进行分水岭变换，通过粘性液体淹没图像地貌的流溢特性，建立图像地貌特征参数（高度级、体积等）与粘性流体温度以及粘性度之间的关系。从而使得对于目标区域采用温度较高的低粘度液体进行淹没，而对于非规则细节和噪声则采用温度较低的高粘性度液体进行淹没。在此模型的基础上，通过大小受特征参数控制的可变粘性结构元素对图像进行形态学运算，模拟并实现粘性液体淹没图像地貌的过程，一方面消除过分割，另一方面，实现目标区域轮廓的准确定位。 在参数化粘性形态学分水岭分割理论方法的基础上，将其应用于重离子放疗计划中肿瘤区域的分割，防止因分割定位不准确，造成对患者正常组织的损伤或肿瘤的遗漏。

中文关键词： 图像分割；参数化分水岭变换；粘性流体；可变结构元素；肿瘤分割

英文摘要： Morphological watershed transform is an efficient way to segment image. Especially, it can produce closed and precise object contours. However, it often results in over-segmentation when it is directly applied to an original image. Usually, over-segmentation can be avoided in some degree by using pre-filtering, whereas the position of the segmented region contours may be offset. For the purpose of segmenting image without over-segmentation and region contours position bias, parameterized viscous morphological watershed segmentation is proposed, in which water is replaced by viscous fluid to perform watershed transform. It is well known that the viscousity of viscous fluid is determined by the flooding temperature. When temperature is higher, viscous fluid can fill the small irregulated relief, while at a lower temperature, it can only enter the larger relief. Such principle inspire us that one can adopt higher temperature fluid to flood the objects relief while lower temperature fluid to flood small image details and noise. By this way, irregulated local minimum can be eliminated and the relief minimum correspoding to object are preserved. However, how to control the viscousity of viscous fluid and what image feature parameter can be severved to control the viscousity are the key problems, In order to solve thes

英文关键词： Image segmentation；parameterized watershed transform；viscous fluid；variational structure element；tumor segmentation