unravel.region_stats.rstats_mean_IF_in_segmented_voxels module#

Use rstats_mean_IF_in_seg from UNRAVEL to measure mean intensity of immunofluorescence (IF) staining in brain regions in segmented voxels (in tissue space).

Prereqs:

seg_ilastik for segmentation
reg for registration

Inputs:

rel_path/fluo_image or rel_path/fluo_img_dir
rel_path/seg_img.nii.gz in tissue space (1st glob match processed)
path/atlas.nii.gz to warp to tissue space

Output:

./sample??/seg_dir/sample??_seg_dir_regional_mean_IF_in_seg.csv

Note

This uses full resolution images (i.e., the raw IF image and a segmentation from seg_ilastik)

Next steps:: utils_agg_files -i seg_dir/sample??_seg_dir_regional_mean_IF_in_seg.csv rstats_mean_IF_summary

Usage#

rstats_mean_IF_in_seg -i *.czi -s seg_dir/sample??_seg_dir.nii.gz -a path/atlas.nii.gz [-o seg_dir/sample??_seg_dir_regional_mean_IF_in_seg.csv] [–region_ids 1 2 3] [-c 1] [Optional output: -n rel_path/native_image.zarr] [-fri autofl_50um_masked_fixed_reg_input.nii.gz] [-inp nearestNeighbor] [-ro reg_outputs] [-r 50] [-md parameters/metadata.txt] [-zo 0] [-mi] [-v]

unravel.region_stats.rstats_mean_IF_in_segmented_voxels.parse_args()[source]#

unravel.region_stats.rstats_mean_IF_in_segmented_voxels.calculate_mean_intensity(IF_img, ABA_seg, args)[source]#

Calculates mean intensity for each region in the atlas.

Parameters:

IF_img (np.ndarray) – 3D image of immunofluorescence staining.
ABA_seg (np.ndarray) – 3D image of segmented brain regions.
args (argparse.Namespace) – Command line arguments.

Returns:

{region_id: mean_IF_in_seg}

Return type:

mean_intensities_dict

unravel.region_stats.rstats_mean_IF_in_segmented_voxels.write_to_csv(data, output_path)[source]#: Writes the data to a CSV file.

unravel.region_stats.rstats_mean_IF_in_segmented_voxels.main()[source]#