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Nonrigid registration for evaluating locoregional therapy of hepatocellular carcinoma

机译:非刚性注册评估肝细胞癌局部治疗

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The assessment of the treated margin with locoregional therapy (LT), for hepatocellular carcinoma (HCC), is the common method for predicting HCC recurrence in most hospital. However, tumors sometimes cannot be removed clearly with LT in limited conditions. The therapeutic efficiency of HCC is often evaluated by comparing 2D fusion images of computed tomography (CT) or magnetic resonance imaging (MRI) between the preoperation and the postoperation. However, judgment about whether the tumors exist in the treated margin after LT by using 2D slices sometimes is difficult. It is desirable to develop a suitable image registration algorithm to automatically align the two volumes in order to transform the treated margin of the postoperative volume to the tumor of the preoperative volume to assess the therapeutic efficiency after treatment of HCC. With taking these into consideration, this paper proposed an automatic 3D fusion imaging approach for medical image by using the nonrigid registration method that aligning an ablative margin — that is the treated margin after LT, onto the locations of HCC. In our registration algorithm, a rigid global transformation combined with localized B-spline is used to estimate the significant nonrigid motions of the liver between before and after LT. Our proposed approach can ensure the feasibility, the accuracy and the efficacy to assess the treated margin for HCC. Furthermore, this method can be adapted to register multi-modality medical images. We demonstrate the effectiveness of our proposed method by comparing the difference criterions of fusion evaluation on medical images. The results clearly indicate that our method extremely useful in the evaluation of the treated margin, in addition, it remain the motion and local deformation of the volume.
机译:局部区域疗法(LT)对肝细胞癌(HCC)的治疗余量的评估是大多数医院预测HCC复发的常用方法。但是,有时在有限的条件下用LT不能清晰地清除肿瘤。通常通过比较术前和术后之间的计算机断层扫描(CT)或磁共振成像(MRI)的2D融合图像来评估HCC的治疗效率。然而,有时难以通过使用2D切片来判断在LT后的治疗边缘是否存在肿瘤。期望开发合适的图像配准算法以自动对准两个体积,以便将手术后体积的治疗边缘转换为手术前体积的肿瘤,以评估HCC治疗后的治疗效率。考虑到这些因素,本文提出了一种使用非刚性配准方法对医学图像进行自动3D融合成像的方法,该方法将消融边缘(即LT后的治疗边缘)对准HCC的位置。在我们的配准算法中,结合局部B样条的刚性全局变换用于估计LT前后肝脏的明显非刚性运动。我们提出的方法可以确保可行性,准确性和有效性,以评估HCC的治疗余量。此外,该方法可适于配准多模态医学图像。我们通过比较医学图像融合评估的不同标准来证明我们提出的方法的有效性。结果清楚地表明,我们的方法在评估已处理边距方面非常有用,此外,它还保留了体积的运动和局部变形。

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