background_estimation¶
-
nighres.intensity.
background_estimation
(image, distribution='exponential', ratio=0.001, skip_zero=True, iterate=True, dilate=0, threshold=0.5, save_data=False, overwrite=False, output_dir=None, file_name=None)[source]¶ Background Estimation
Estimates image background by robustlyfitting various distribution models
Parameters: - image (niimg) – Input image
- distribution ({'exponential','half-normal'}) – Distribution model to use for the background noise
- ratio (float, optional) – Robustness ratio for estimating image intensities
- skip_zero (bool, optional) – Whether to consider or skip zero values
- iterate (bool, optional) – Whether to run an iterative estimation (preferred, but sometimes unstable)
- dilate (int, optional) – Number of voxels to dilate or erode in the final mask
- save_data (bool) – Save output data to file (default is False)
- overwrite (bool) – Overwrite existing results (default is False)
- output_dir (str, optional) – Path to desired output directory, will be created if it doesn’t exist
- file_name (str, optional) – Desired base name for output files with file extension (suffixes will be added)
Returns: Dictionary collecting outputs under the following keys (suffix of output files in brackets)
- masked (niimg): The background-masked input image
- proba (niimg): The probability map of the foreground
- mask (niimg): The mask of the foreground
Return type: Notes
Original Java module by Pierre-Louis Bazin.