Source code for drymass.threshold

There are two types of thresholding done in DryMass.

1. Thresholding of the `sensor image` which is required by the
   detection of the phase object ROIs
   (``[roi]: threshold`` configuration parameter)
2. Thresholding of the `individual ROIs` for determining the masked
   area used for ROI background correction
   (``[bg]: amplitude binary threshold``
   and ``[bg]: phase binary threshold`` configuration parameters)
import warnings

import numpy as np
import skimage.filters as skfilters

[docs]def image2mask(image, value_or_method, invert=False): """Convert an image to a binary mask for background correction If `invert` is False, the threshold value is included in the resulting array. Parameters ---------- image: 2d np.ndarray Input image value_or_method: float or str Either a threshold value or a string naming a filter method in :mod:`skimage.filters`. invert: bool Invert the resulting boolean array """ if isinstance(value_or_method, str): if value_or_method.startswith("threshold_"): value_or_method = value_or_method[10:] warnings.warn("Use of the name of the thresholding function " "from skimage is deprecated. Please use " " '{}' instead!".format(value_or_method), DeprecationWarning) method = threshold_dict[value_or_method] bw = image >= method(image) else: bw = image >= value_or_method if invert: return ~bw else: return bw
[docs]def threshold_drymass_nuclei(image): """Threshold filter for segmenting cell nuclei in phase images Cell nuclei have a low refractive index, but the nucleoli within the nuclei usually have a very high refractive index. As a result, conventional thresholding algorithms either cannot detect the nuclei reliably or segment the nucleoli only. This thresholding filter copes with the situation by "pulling down" the top 1% of the phase data and taking the threshold at 20% of the maximum phase relative to the mean of the original phase data. """ image = image.copy() mean = np.mean(image) size = image.size # ignore the top 1% counter = 0 maxim = np.max(image) while counter < size // 100: maxid = image == maxim counter += np.sum(maxid) maxim = np.max(image[~maxid]) image[maxid] = maxim # take 20% as threshold value thresh = mean + .2 * (maxim-mean) return thresh
[docs]def threshold_li(image): """Li threshold optimized for cells in QPI""" return skfilters.threshold_li(image, initial_guess=np.percentile(image, q=95))
#: Dictionary containing all thresholding methods available in DryMass threshold_dict = { 'dm-nuclei': threshold_drymass_nuclei, 'isodata': skfilters.threshold_isodata, 'li': threshold_li, 'mean': skfilters.threshold_mean, 'minimum': skfilters.threshold_minimum, 'otsu': skfilters.threshold_otsu, 'triangle': skfilters.threshold_triangle, 'yen': skfilters.threshold_yen, } #: Available thresholding method names; #: The thresholding methods are either defined in this module #: (see `threshold_*` methods) or taken from :mod:`skimage.filters`. available_thresholds = sorted(threshold_dict.keys())