基于平移旋转不变的塔式分解和模糊梯度场的医学图像配准

Medical Image Registration Based on Translation and Rotation-Invariant Multiresolution Decomposition and Fuzzy Gradient Field

为了提高医学图像配准的精度和速度,提出一种改进的圆周对称多分辨率分解算法,用环形带通滤波器代替高通滤波器,使各尺度的子带都具有平移和旋转不变性.不丢失信息的前提下,降低计算的冗余度.塔式分解的低频子带能量集中,用互信息进行配准;高频子带提供重要的解剖结构信息,构造基于边缘信息的模糊梯度场,并用模糊贴近度作为相似性测度,与互信息相结合.实验结果验证了新的金字塔算法的有效性,并且可以实现多模态医学图像的配准,结合模糊梯度场的配准算法提高了算法的鲁棒性,快速准确稳定地实现医学图像配准.

To improve the medical image registration efficiency and accuracy,a new multiresolution analysis,improved circular symmetric muitiresolution decomposition is proposed. An annular band-pass filter takes place of the high-pass filter in the circular symmetric mulfiresolution analysis to reduce the redundancy. All the subbands possess translation- and rotation- invariance. Low-pass subband has noise-removing property and is suitable to image registration based on mutual information. Band-pass subband has more significant structural information, which establishes image fuzzy gradient field and constructs the fuzzy approach degree. A coarse-to-fine procedure is adopted to utilize these features to achieve registration procedure.Experiments demonstrate the good performance of the proposed novel pyramid decomposition. The local extrerna can be reduced and these characteristics of combined measures yield more robust and accurate registration results.