about DSC

[Tara-Liu]

Do you have any code for calculating DSC evaluation indicators

[cwmok]

Hi @Tara-Liu,

Here you go.

def dice(im1, atlas):
    unique_class = np.unique(atlas)
    dice = 0
    num_count = 0
    for i in unique_class:
        if (i == 0) or ((im1 == i).sum() == 0) or ((atlas == i).sum() == 0):
            continue

        sub_dice = np.sum(atlas[im1 == i] == i) * 2.0 / (np.sum(im1 == i) + np.sum(atlas == i))
        dice += sub_dice
        num_count += 1
    return dice / num_count

[Tara-Liu]

Hi @Tara-Liu,

Here you go.

def dice(im1, atlas):
    unique_class = np.unique(atlas)
    dice = 0
    num_count = 0
    for i in unique_class:
        if (i == 0) or ((im1 == i).sum() == 0) or ((atlas == i).sum() == 0):
            continue

        sub_dice = np.sum(atlas[im1 == i] == i) * 2.0 / (np.sum(im1 == i) + np.sum(atlas == i))
        dice += sub_dice
        num_count += 1
    return dice / num_count

Thank you. May I ask if the input parameters of this code are fixed img and moving img after registration? In addition, I noticed that there is also an evaluation index about the Jacobian determinant in the paper, do you have the corresponding code

[cwmok]

@Tara-Liu

May I ask if the input parameters of this code are fixed img and moving img after registration?

The inputs for the function are the label map (segmentation map) for moving and fixed image.

In addition, I noticed that there is also an evaluation index about the Jacobian determinant in the paper, do you have the corresponding code

I use the code provided by the Learn2Reg challenge.
https://github.com/MDL-UzL/L2R/blob/fc713f5baf107932a8f72ab55484bf7ac3210b57/evaluation/utils.py#L10C1-L37C18