Chen Q S, Defrise M, Deconinck F
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.
Med Phys. 1996 Jun;23(6):877-85. doi: 10.1118/1.597730.
A parameter accumulation method based on the Hough transformation is proposed to register three-dimensional (3-D) multimodality medical images. The estimation of registration parameters is decomposed into separate estimations of rotation, using directional vectors, and translation, using positional vectors. Similarly, the rotation parameters are decomposed into the rotation axis and angle, which are then estimated separately. This kind of decomposition reduces the parametric dimension and improves the computing efficiency which has been a major concern in implementing the Hough transformation. When 3-D rotation is involved, evaluating registration error is not straightforward. This paper introduces an equivalent error angle as a criterion to evaluate the performance of 3-D registration methods. Experimental results indicate that a least-squares fitting is superior to the parameter accumulation with data contaminated by additive noise only. When mismatched feature points (outliers) exist in the data set, however, the parameter accumulation approach is more accurate. The application of the proposed approach to the registration of 3-D PET and CT images is demonstrated.
提出了一种基于霍夫变换的参数累积方法来配准三维（3-D）多模态医学图像。配准参数的估计被分解为使用方向向量的旋转估计和使用位置向量的平移估计。类似地，旋转参数被分解为旋转轴和角度，然后分别进行估计。这种分解降低了参数维度，提高了计算效率，而计算效率一直是实施霍夫变换时的主要关注点。当涉及三维旋转时，评估配准误差并不直接。本文引入等效误差角作为评估三维配准方法性能的标准。实验结果表明，仅在数据被加性噪声污染时，最小二乘拟合优于参数累积。然而，当数据集中存在不匹配的特征点（离群值）时，参数累积方法更准确。展示了所提出方法在三维正电子发射断层扫描（PET）和计算机断层扫描（CT）图像配准中的应用。
