cBrainMRIPrePro.utils package

Subpackages

Submodules

cBrainMRIPrePro.utils.files module

Author: Alexandre CARRE
Created on: Nov 23, 2020
cBrainMRIPrePro.utils.files.check_is_nii_exist(input_file_path)[source]

Check if a directory exist.

Parameters

input_file_path (str) – string of the path of the nii or nii.gz.

Return type

str

Returns

string if exist, else raise Error.

cBrainMRIPrePro.utils.files.check_isdir(input_dir)[source]

Check if a directory exist.

Parameters

input_dir (str) – string of the path of the input directory.

Return type

str

Returns

string if exist, else raise NotADirectoryError.

cBrainMRIPrePro.utils.files.load_nifty_volume_as_array(input_path_file)[source]

Load nifty image into numpy array [z,y,x] axis order. The output array shape is like [Depth, Height, Width].

Parameters

input_path_file (str) – input path file, should be ‘.nii’ or ‘.nii.gz’

Return type

Tuple[ndarray, Tuple[Tuple, Tuple, Tuple]]

Returns

a numpy data array, (with header)

cBrainMRIPrePro.utils.files.safe_file_name(file_name)[source]

Remove any potentially dangerous or confusing characters from the file name by mapping them to reasonable substitutes.

Parameters

file_name (str) – name of the file.

Return type

str

Returns

name of the file corrected.

cBrainMRIPrePro.utils.files.save_to_nii(im, header, output_dir, filename, mode='image', gzip=True)[source]

Save numpy array to nii.gz format to submit.

Parameters

  • im (ndarray) – array numpy

  • header ((tuple, tuple, tuple)) – header metadata (origin, spacing, direction).

  • output_dir (str) – Output directory.

  • filename (str) – Filename of the output file.

  • mode (str) – save as ‘image’ or ‘label’

  • gzip (bool) – zip nii (ie, nii.gz)

Return type

None

cBrainMRIPrePro.utils.files.split_filename(file_name)[source]

Split file_name into folder path name, basename, and extension name.

Parameters

file_name (str) – full path

Return type

Tuple[str, str, str]

Returns

path name, basename, extension name

cBrainMRIPrePro.utils.image_processing module

Author: Alexandre CARRE
Created on: Nov 23, 2020
cBrainMRIPrePro.utils.image_processing.fill_mask(mask_arr)[source]

Fill a 3D mask array. Useful when use a threshold function and need to fill hole

Parameters

mask_arr (ndarray) – mask to fill

Return type

ndarray

Returns

mask filled

cBrainMRIPrePro.utils.image_processing.get_mask(input_array)[source]

Get a (head) mask. Based on Otsu threshold and noise reduced. Then result mask is holes filled.

Parameters

input_array (ndarray) – input image array

Return type

ndarray

Returns

binary head mask

cBrainMRIPrePro.utils.image_processing.invert_min_max_scaling(input_array_scaled, scale_, min_)[source]

Invert min max scaling

Parameters

  • input_array_scaled (ndarray) – input image array scaled

  • scale – Per pixels/voxels relative scaling of the data.

  • min – Per pixels/voxels minimum seen in the data

Return type

ndarray

Returns

input image array unscaled

cBrainMRIPrePro.utils.image_processing.min_max_scaling(input_array, scaling_range=(10, 100))[source]

Transform image input pixels/voxels to a given range. (type min-max scaler)

Parameters

  • input_array (ndarray) – input image array

  • scaling_range (Tuple[int, int]) – min, max = feature_range

Return type

Tuple[ndarray, float, float]

Returns

image_scaled, min, scale

cBrainMRIPrePro.utils.image_processing.zscore_normalize(input_array, scaling_factor=1, mask=None)[source]

Function to normalize array with Z-Score. Normalize a target image by subtracting the mean of the whole brain and dividing by the standard deviation.

Parameters

  • input_array (Union[ndarray, str]) – input array image to normalize

  • scaling_factor (int) – scaling factor to apply to normalization

  • mask (Union[ndarray, str, None]) – input mask where to apply the normalization. If not provided default will be in non zero value

Return type

ndarray

Returns

input array normalize

Module contents