对腹部CT和锥束CT(CBCT)图像中肝脏肿瘤的精确定位，以及放疗时肿瘤的自适应追踪是早期肝癌立体定向放疗计划制定和精准治疗的关键。针对CT和CBCT图像中肝脏肿瘤难以精确分割的问题，提出腹部MRI图像引导的CT和CBCT图像肿瘤自动勾画方法。首先基于多尺度3D-CNN和全连接CRF实现MRI图像肿瘤的准确分割，然后根据肝脏主血管结构实现腹部多模态图像粗配准，最后研究基于图割求解的MRF精配准框架，准确勾画CT和CBCT图像中肝肿瘤区域。针对放疗时因呼吸运动、胃肠蠕动等导致的靶区定位不准，提出肝脏肿瘤自适应追踪方法。首先基于多分辨率B样条形变配准构建初始呼吸运动模型，然后根据肿瘤在分次间和分次内的运动情况对该模型进行基线和形变向量场更新，实现对肿瘤的自适应追踪。该研究将辅助医生精确定位肝癌放疗靶区并制定放疗计划，提高放疗精度，减少射线对正常组织和器官的损伤，提升患者的生存率，改善生活质量。

Accurate localization of liver tumor in abdominal CT and cone beam CT (CBCT), and adaptive tumor tracking during radiotherapy are essential to stereotactic body radiation therapy planning and high-precision treatment for patients with early hepatocellular carcinoma. Aiming at the inseparable of liver tumor from CT and CBCT sequences, the project proposes an abdominal MRI sequences guided automatic sketching method. Firstly, liver tumor is segmented accurately from MRI sequences by combining the multi-scale based 3D Convolutional Neural Networks (3D-CNN) and fully connected Conditional Random Field (CRF). Then, the coarse registration of multi-modality images is conducted according to the structure of liver vessels. Next, the Markov Random Field (MRF) modeled fine registration framework is optimized by the Graph-Cut algorithm to acquire accurate liver tumor contours in CT and CBCT images. Aiming at the inaccurate localization of target in radiation therapy because of the respiratory motion and gastrointestinal motility, the project proposes an adaptive liver tumor tracking method. Firstly, a multi-resolution B-spline deformable image registration algorithm is applied to construct the original respiratory motion model. Next, to track the tumor adaptively, the baseline and deformable vector fields (DVFs) of the motion model are updated respectively according to the inter-fraction and intra-fraction tumor motion. This project will not only help the radiologists locate liver tumor target accurately and therefore formulate radiotherapy planning reasonably, but also contribute to improving the precision of radiotherapy, preventing normal tissue and organs from being exposed to particle beams, and thus, improving overall survival and quality of life for patients with early hepatocellular carcinoma.