usage: __main__.py [-h] [--data_type DATA_TYPE] [--exclude_background]
[-v [{DEBUG,INFO,WARNING}]] [-f]
{lower_threshold,upper_threshold,lower_threshold_eq,upper_threshold_eq,lower_threshold_otsu,upper_threshold_otsu,lower_clip,upper_clip,absolute_value,round,ceil,floor,normalize_sum,normalize_max,log_10,log_e,convert,invert,addition,subtraction,multiplication,division,mean,std,correlation,union,intersection,difference,concatenate,dilation,erosion,closing,opening,blur}
in_args [in_args ...] out_image
Performs an operation on a list of images. The supported operations are
listed below.
This script is loading all images in memory, will often crash after a few
hundred images.
Some operations such as multiplication or addition accept float value as
parameters instead of images.
> scil_volume_math.py multiplication img.nii.gz 10 mult_10.nii.gz
Formerly: scil_image_math.py
lower_threshold: IMG THRESHOLD
All values below the threshold will be set to zero.
All values above the threshold will be set to one.
upper_threshold: IMG THRESHOLD
All values below the threshold will be set to one.
All values above the threshold will be set to zero.
Equivalent to lower_threshold followed by an inversion.
lower_threshold_eq: IMG THRESHOLD
All values below the threshold will be set to zero.
All values above or equal the threshold will be set to one.
upper_threshold_eq: IMG THRESHOLD
All values below or equal the threshold will be set to one.
All values above the threshold will be set to zero.
Equivalent to lower_threshold followed by an inversion.
lower_threshold_otsu: IMG
All values below or equal to the Otsu threshold will be set to zero.
All values above the Otsu threshold will be set to one.
(Otsu's method is an algorithm to perform automatic image thresholding
of the background.)
upper_threshold_otsu: IMG
All values below the Otsu threshold will be set to one.
All values above or equal to the Otsu threshold will be set to zero.
Equivalent to lower_threshold_otsu followed by an inversion.
lower_clip: IMG THRESHOLD
All values below the threshold will be set to threshold.
upper_clip: IMG THRESHOLD
All values above the threshold will be set to threshold.
absolute_value: IMG
All negative values will become positive.
round: IMG
Round all decimal values to the closest integer.
ceil: IMG
Ceil all decimal values to the next integer.
floor: IMG
Floor all decimal values to the previous integer.
normalize_sum: IMG
Normalize the image so the sum of all values is one.
normalize_max: IMG
Normalize the image so the maximum value is one.
log_10: IMG
Apply a log (base 10) to all non zeros values of an image.
log_e: IMG
Apply a natural log to all non zeros values of an image.
convert: IMG
Perform no operation, but simply change the data type.
invert: IMG
Operation on binary image to interchange 0s and 1s in a binary mask.
addition: IMGs
Add multiple images together.
subtraction: IMG_1 IMG_2
Subtract first image by the second (IMG_1 - IMG_2).
multiplication: IMGs
Multiply multiple images together (danger of underflow and overflow)
division: IMG_1 IMG_2
Divide first image by the second (danger of underflow and overflow)
Ignore zeros values, excluded from the operation.
mean: IMGs
Compute the mean of images.
If a single 4D image is provided, average along the last dimension.
std: IMGs
Compute the standard deviation average of multiple images.
If a single 4D image is provided, compute the STD along the last
dimension.
correlation: IMGs
Computes the correlation of the 3x3x3 neighborhood of each voxel, for
all pair of input images. The final image is the average correlation
(through all pairs).
For a given pair of images
- Background is considered as 0. May lead to very high correlations
close to the border of the background regions, or very poor ones if the
background in both images differ.
- Images are zero-padded. For the same reason as higher, may lead to
very high correlations if you have data close to the border of the
image.
- NaN values (if a voxel's neighborhood is entirely uniform; std 0) are
replaced by
- 0 if at least one neighborhood was entirely containing background.
- 1 if the voxel's neighborhoods are uniform in both images
- 0 if the voxel's neighborhoods is uniform in one image, but not
the other.
UPDATE AS OF VERSION 2.0: Random noise was previously added in the
process to help avoid NaN values. Now replaced by either 0 or 1 as
explained above.
union: IMGs
Operation on binary image to keep voxels, that are non-zero, in at
least one file.
intersection: IMGs
Operation on binary image to keep the voxels, that are non-zero,
are present in all files.
difference: IMG_1 IMG_2
Operation on binary image to keep voxels from the first file that are
not in the second file (non-zeros).
concatenate: IMGs
Concatenate a list of 3D and 4D images into a single 4D image.
dilation: IMG, VALUE
Binary morphological operation to spatially extend the values of an
image to their neighbors. VALUE is in voxels.
If VALUE is 0, the dilation is repeated until the result does not
change anymore.
erosion: IMG, VALUE
Binary morphological operation to spatially shrink the volume contained
in a binary image. VALUE is in voxels.
If VALUE is 0, the erosion is repeated until the result does not
change anymore.
closing: IMG, VALUE
Binary morphological operation, dilation followed by an erosion.
opening: IMG, VALUE
Binary morphological operation, erosion followed by a dilation.
blur: IMG, VALUE
Apply a gaussian blur to a single image. VALUE is sigma, the standard
deviation of the Gaussian kernel.
positional arguments:
{lower_threshold,upper_threshold,lower_threshold_eq,upper_threshold_eq,lower_threshold_otsu,upper_threshold_otsu,lower_clip,upper_clip,absolute_value,round,ceil,floor,normalize_sum,normalize_max,log_10,log_e,convert,invert,addition,subtraction,multiplication,division,mean,std,correlation,union,intersection,difference,concatenate,dilation,erosion,closing,opening,blur}
The type of operation to be performed on the images.
in_args The list of image files or parameters. Refer to each operation's documentation of the expected arguments.
out_image Output image path.
options:
-h, --help show this help message and exit
--data_type DATA_TYPE
Data type of the output image. Use the format:
uint8, int16, int/float32, int/float64.
--exclude_background Does not affect the background of the original images.
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
-f Force overwriting of the output files.