Gibbs P, Buckley D L, Blackband S J, Horsman A
Department of Medical Physics, Royal Hull Hospitals NHS Trust, UK.
Phys Med Biol. 1996 Nov;41(11):2437-46. doi: 10.1088/0031-9155/41/11/014.
Accurate tumour volume measurement from MR images requires some form of objective image segmentation, and therefore a certain degree of automation. Manual methods of separating data according to the various tissue types which they are thought to represent are inherently prone to operator subjectivity and can be very time consuming. A segmentation procedure based on morphological edge detection and region growing has been implemented and tested on a phantom of known adjustable volume. Comparisons have been made with a traditional data thresholding procedure for the determination of tumour volumes on a set of patients with intracerebral glioma. The two methods are shown to give similar results, with the morphological segmentation procedure having the advantages of being automated and faster.
从磁共振图像中准确测量肿瘤体积需要某种形式的客观图像分割，因此需要一定程度的自动化。根据数据所代表的各种组织类型手动分离数据的方法本质上容易受到操作者主观因素的影响，并且可能非常耗时。一种基于形态学边缘检测和区域生长的分割程序已经实现，并在已知可调节体积的模型上进行了测试。已将其与传统的数据阈值化程序进行比较，以确定一组脑内胶质瘤患者的肿瘤体积。结果表明，这两种方法给出的结果相似，形态学分割程序具有自动化和速度更快的优点。
