Is it possible to compute 2D Hessian value for each slice in a 3D medical array?

Hi, I am trying to compute 2-dimention hessian value for each slice in a 3D array. I succeed computing 3D hessian value for a 3D image or 2D hessian value for a single slice by using itk.MultiScaleHessianBasedMeasureImageFilter. But is it possible to perform Hessian Augmentation simultaneously for all the slices in a 3D array? I know I could achieve it by writing a for-loop, which is, however, very time-consuming. Thank you for your replies.

Here is how I compute 2D hessian value

def hessian2D(array2d):
    print("*****Hessian-vessel starts!*****")
    start_time = time()
    dimention = len(array2d.shape)
    img_itk = itk.GetImageFromArray(array2d)

    # 1
    sigma_minimum = 0.2
    sigma_maximum = 1  # 3.
    number_of_sigma_steps = 8
    ImageType = type(img_itk)
    Dimension = img_itk.GetImageDimension()
    HessianPixelType = itk.SymmetricSecondRankTensor[itk.D, Dimension]
    HessianImageType = itk.Image[HessianPixelType, Dimension]
    objectness_filter = itk.HessianToObjectnessMeasureImageFilter[HessianImageType, ImageType].New()
    multi_scale_filter = itk.MultiScaleHessianBasedMeasureImageFilter[ImageType, HessianImageType, ImageType].New()
    output = multi_scale_filter.GetOutput()
    output_array = itk.GetArrayFromImage(output)
    end_time = time()
    print("Hessian-vessel finished, duration:{}s".format(end_time - start_time))
    return output_array

Hello @Fivethousand,

Possibly look at the SliceBySliceFilter. I’m not sure it is available in ITK’s Python wrapping but likely. The MultiScaleHessianBasedMeasureImageFilter is not available in SimpleITK.

Finally you can always use Python multiprocessing to work on multiple slices in parallel.

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Thank you for your reply, I just notice that most of time is used in C compilation when initializing the

MultiScaleHessianBasedMeasureImageFilter . And the time of iterating each slice could be totally ignored.