论文部分内容阅读
目的:为了有效解决单独使用正电子发射断层扫描(PET)和核磁共振成像(MRI)影像勾画大体肿瘤靶区(GTV)存在的肿瘤、水肿及其周围正常组织区分难题。方法:首先选取PET图像上包含肿瘤区域的感兴趣区域(ROI)中标准摄取值(SUV)最大的体素点作为肿瘤区域生长算法的初始种子点,在PET和MRI影像上分别进行第一阶段自适应区域生长。然后从其勾画的肿瘤PET靶区内自动获取肿瘤的最小SUV值,并联合肿瘤MRI靶区自适应区域生长的最佳阈值构建第二阶段肿瘤PET和MRI联合区域生长准则,进行第二阶段区域生长,完成PET与MRI融合靶区勾画。结果:与单独使用PET和单独使用MRI影像的自适应区域生长分割结果相比,参考两位经验丰富的临床放疗专家手工勾画的鼻咽癌MRI GTV,本文方法勾画的融合GTV与MRI GTV具有最高相似性,且同时具有较高灵敏性和较高特异性。结论:本文方法可实现头颈部肿瘤PET与MRI融合大体肿瘤靶区自适应高精度勾画。
OBJECTIVE: To effectively solve the problem of differentiation of tumor, edema and surrounding normal tissue by using positron emission tomography (PET) and magnetic resonance imaging (MRI) to outline the general tumor target area (GTV). Methods: First, the voxel with the highest standard in-region (ROI) of the ROI on the PET image was selected as the initial seed point of the tumor growth algorithm. The first stage was performed on PET and MRI images respectively Adaptive area growth. Then the minimum SUV value of the tumor was obtained automatically from the tumor PET target outlined by it and the optimal threshold of the growth of the adaptive region of the MRI target region was constructed to build the joint growth guideline of PET and MRI in the second phase. Growth, completion of PET and MRI fusion target area outlined. Results: Compared with the results of adaptive region growth segmentation using PET alone and MRI images alone, referring to MRI GTV of nasopharyngeal carcinoma hand-sketched by two experienced clinical radiotherapy experts, the fusion GTV and MRI GTV outlined by this method have the highest Similarity, and at the same time has a higher sensitivity and higher specificity. Conclusion: This method can be used to achieve high-precision contouring of PET and MRI fusion general tumor target area in head and neck cancer.