SimpleITK互信息医学图像配准代码

以下是使用SimpleITK进行互信息医学图像配准的Python代码示例：

import SimpleITK as sitk

# 读取待配准图像和参考图像
fixed_image = sitk.ReadImage('fixed_image.nii.gz')
moving_image = sitk.ReadImage('moving_image.nii.gz')

# 设置配准参数
registration_method = sitk.ImageRegistrationMethod()

# 设置相似性度量为归一化互信息
registration_method.SetMetricAsMattesMutualInformation(numberOfHistogramBins=50)

# 设置优化方法为基于萤火虫算法改进的优化策略
registration_method.SetOptimizerAsFireflyAlgorithm(maximumNumberOfIterations=100)

# 设置插值器为BSpline插值器
registration_method.SetInterpolator(sitk.sitkBSpline)

# 设置变换模型为仿射变换
initial_transform = sitk.CenteredTransformInitializer(fixed_image, moving_image, sitk.AffineTransform(3))
registration_method.SetInitialTransform(initial_transform)

# 进行配准
final_transform = registration_method.Execute(fixed_image, moving_image)

# 将变换应用于待配准图像
resampled_image = sitk.Resample(moving_image, fixed_image, final_transform, sitk.sitkLinear, 0.0, moving_image.GetPixelID())

# 保存配准结果
sitk.WriteImage(resampled_image, 'output.nii.gz')