基于形变模型分割方法的CT图像肝脏肿瘤分割

Segmentation of Liver Tumors in CT Images Based on Deformable Model Segmentation

在肝脏肿瘤疾病计算机辅助检测及诊断过程中,CT图像肝脏肿瘤分割属于是重要环节,因此在临床中CT图像肝脏肿瘤分割具有重要研究意义。传统几何形变模型在对比度较高的图像中应用更为适合,但是CT图像肝脏肿瘤通常情况下灰度不均匀、对比度偏低,没有良好的分割效果。基于这一问题,在对传统几何形变模型研究技术上,探讨CT图像肝脏肿瘤的新型形变模型分割方法。

In the process of computer-aided detection and diagnosis of liver tumors,the segmentation of liver tumors on CT images is an important part,so it is of great significance to study the segmentation of liver tumors on CT images in clinic.Traditional geometric deformation models are more suitable for high contrast images.However,in CT images of liver tumors,the gray scale is not uniform and the contrast is low,so there is no good segmentation effect.Based on this problem,a new segmentation method for liver tumors in CT images is discussed in terms of the traditional geometric deformation model technology.