def scale_input_to_original_shape(img4d, dataset, resolution="1.25mm"):
"""
Scale input image to original resolution and pad/cut image to make it original size.
This is not generic but optimised for some specific datasets.
Args:
img4d: (x, y, z, classes)
dataset: HCP|HCP_32g|TRACED|Schizo
resolution: 1.25mm|2mm|2.5mm
Returns:
(x_original, y_original, z_original, classes)
"""
if resolution == "1.25mm":
if dataset == "HCP": # (144,144,144)
# no resize needed
return img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[146, 174, 146, img4d.shape[3]], pad_value=0) # (146, 174, 146, none)
elif dataset == "HCP_32g": # (144,144,144)
# no resize needed
return img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[146, 174, 146, img4d.shape[3]], pad_value=0) # (146, 174, 146, none)
elif dataset == "TRACED": # (78,93,75)
raise ValueError("resolution '1.25mm' not supported for dataset 'TRACED'")
elif dataset == "Schizo": # (144,144,144)
img4d = img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[145, 174, 145, img4d.shape[3]], pad_value=0) # (145, 174, 145, none)
return img_utils.resize_first_three_dims(img4d, zoom=0.62) # (91,109,91)
elif resolution == "2mm":
if dataset == "HCP": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "HCP_32g": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "HCP_2mm": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "TRACED": # (78,93,75)
raise ValueError("resolution '2mm' not supported for dataset 'TRACED'")
elif resolution == "2.5mm":
if dataset == "HCP": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77,:,4:77, :] # (73, 87, 73, none)
elif dataset == "HCP_2.5mm": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77,:,4:77,:] # (73, 87, 73, none)
elif dataset == "HCP_32g": # ((80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77, :, 4:77, :] # (73, 87, 73, none)
elif dataset == "TRACED": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 7, 0, 0]),
[80, 93, 80, img4d.shape[3]], pad_value=0) # (80,93,80,none)
return img4d[1:79, :, 3:78, :] # (78,93,75,none)
def scale_input_to_world_shape(img4d, dataset, resolution="1.25mm"):
'''
Scale input image to original resolution and pad/cut image to make it original size
:param img4d: (x, y, z, userdefined) (userdefined could be gradients or classes)
:param resolution: "1.25mm" / "2mm" / "2.5mm"
:return: img with original size
'''
if resolution == "1.25mm":
if dataset == "HCP": # (144,144,144)
# no resize needed
return img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[146, 174, 146, img4d.shape[3]], pad_value=0) # (146, 174, 146, none)
elif dataset == "HCP_32g": # (144,144,144)
# no resize needed
return img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[146, 174, 146, img4d.shape[3]], pad_value=0) # (146, 174, 146, none)
elif dataset == "TRACED": # (78,93,75)
raise ValueError("resolution '1.25mm' not supported for dataset 'TRACED'")
elif dataset == "Schizo": # (144,144,144)
img4d = img_utils.pad_4d_image_left(img4d, np.array([1, 15, 1, 0]),
[145, 174, 145, img4d.shape[3]], pad_value=0) # (145, 174, 145, none)
return img_utils.resize_first_three_dims(img4d, zoom=0.62) # (91,109,91)
elif resolution == "2mm":
if dataset == "HCP": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "HCP_32g": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "HCP_2mm": # (80,80,80)
return img_utils.pad_4d_image_left(img4d, np.array([5, 14, 5, 0]),
[90, 108, 90, img4d.shape[3]], pad_value=0) # (90, 108, 90, none)
elif dataset == "TRACED": # (78,93,75)
raise ValueError("resolution '2mm' not supported for dataset 'TRACED'")
elif resolution == "2.5mm":
if dataset == "HCP": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77,:,4:77, :] # (73, 87, 73, none)
elif dataset == "HCP_2.5mm": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77,:,4:77,:] # (73, 87, 73, none)
elif dataset == "HCP_32g": # ((80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 4, 0, 0]),
[80, 87, 80, img4d.shape[3]], pad_value=0) # (80,87,80,none)
return img4d[4:77, :, 4:77, :] # (73, 87, 73, none)
elif dataset == "TRACED": # (80,80,80)
img4d = img_utils.pad_4d_image_left(img4d, np.array([0, 7, 0, 0]),
[80, 93, 80, img4d.shape[3]], pad_value=0) # (80,93,80,none)
return img4d[1:79, :, 3:78, :] # (78,93,75,none)