276 lines
11 KiB
Python
276 lines
11 KiB
Python
"""preprocessing of synchrotron images based on telemosToolbox."""
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from catalog import ImageCatalog, Sequence
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from imageengine import IImageEngine
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from imagej.ijimageengine import IJImageEngine, IJImage
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class WhiteEstimator(object):
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def __init__(self, open_size, close_size, average_size):
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"""
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:param int open_size: the diameter of the structuring element used to perform mathematical morphology's opening operator (in pixels)
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:param int close_size: the diameter of the structuring element used to perform mathematical morphology's closing operator (in pixels)
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"""
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self.open_size = open_size
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self.close_size = close_size
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self.average_size = average_size
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def _remove_particles(self, white_estimate):
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IImageEngine.get_instance().perform_gray_morphology(white_estimate, operator='open', structuring_element_shape='square', structuring_element_radius=(self.open_size + 1) / 2)
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IImageEngine.get_instance().perform_gray_morphology(white_estimate, operator='close', structuring_element_shape='square', structuring_element_radius=(self.close_size + 1) / 2)
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def estimate_white(self, sequences, channel_ids, dark=None):
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"""Estimation of the white fluorescence image shape of synchrotron light from experimental images of Telemos microscope.
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:param list(Sequence) sequences: the sequences to consider
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:param list(str) channel_ids: the channels to consider, eg ['DM300_327-353_fluo']
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:param WhiteEstimatorSettings white_estimator_settings:
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:param ImagePlus or None dark:
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:rtype ImagePlus:
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Code adapted from matlab telemosToolbx's estimatedwhiteFluoImageTelemos function
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% this function is specific of Telemos images (DISCO line SOLEIL)
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% acquired using micromanager software linked to imageJ
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%% input
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% nothing : interactive function
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%% output
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% nothing : the final reference fluorescence image is saved on disk
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%% principe
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% NB: MICROMANAGER save images in a structured file folder architecture :
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%
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% root folder : name given by the user
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%
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% subfolders roi(n)_tile1 : n folders for each selected roi
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% or pos(n) : n folders for each selected position
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%
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% display_and_comments.txt : file describing the channels acquired
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%
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% in each subfolder roi(n)_tile1 or Pos(n) :
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% images files with name img_00000000(n)_DM300_327-353_00(p).tif
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% n = number of time
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% p = z focal plane
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% DM300_327-353 = name of the channel
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% metadata.txt : files describing all metadata associated with the
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% acquisition : x, y, z position, camera settings .... etc.
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%
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% (Nb: depending on the date of acquisition, an extension fluo is found or
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% not in the name of fluorescence image. This extension is given in
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% contrast to the visible image.)
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%
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% IMAGES : fluorescence images are considered
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%
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%
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% IMPORTANT:
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% it is expected that in the folders at least several images cover the whole field of view
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% illuminated by the synchrtron light
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% IF IT IS NOT THE CASE, IT WON'T WORK
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%
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% BASIC: the estimated white image is the MAX of the selected images
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% when interactive mode is selected, only first time and first z are
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% proposed
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% for automatic computing, all images are taken into account
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%
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% WHAT IS DONE:
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% 0 - the user chosse the channels that are considered in the estimation of the
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% white fluorescence image
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%
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% 1 - spurious pixels (three lines and columns around the image) are not taken
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% in filtering and replaced by line and column number 4 and end-3
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%
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% 2 - Filtering
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% the estimated dark image is filtered :
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% opening to remove white regions brighter than the low frequency signal that should correspond to synchrotron light shape (should be small)
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% closing to remove black regions that remains (should be small to avoid synchrotron light shape deformation)
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% average filtering
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% the image computed should be used to
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% - to find the best white z plane from the reference white stack
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% acquired for ex. using the so called "Matthieu lame"%
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% - correct images for intensities
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%% use
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% estimatedwhiteFluoImageTelemos
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%% Comments
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% adapted from proposals 20161050 and 20171187
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%% Author
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% MF Devaux
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% INRA BIA
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% PVPP
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%% date
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% 5 octobre 2017:
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% 23 mars 2018
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% 3 septembre 2018 : comments and general case
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% 16 avril 2019: name of function and default filtering values
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% 29 avril 2019 : new comments and spurious pixels
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% 27 mai 2019 : offset dark
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% 4 juin 2019 : replace exist by isfolder or isfile
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% 14 juin : close figure at the end
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"""
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images_file_path = []
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for sequence in sequences:
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for channel_id in channel_ids:
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channel_index = sequence.get_channel_index(channel_id)
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for frame_index in range(sequence.num_frames):
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for z_index in range(sequence.num_slices):
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images_file_path.append(sequence.get_image_file_path(channel_index, frame_index, z_index))
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white_estimate = IImageEngine.get_instance().compute_max(images_file_path)
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# modify spurious pixels on the side of the images
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try:
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IImageEngine.get_instance().replace_border(white_estimate, 3)
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except NotImplementedError as error:
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print('warning: replace_outer_frame is not implemented yet')
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self._remove_particles(white_estimate)
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return white_estimate
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class InteractiveWhiteEstimator(WhiteEstimator):
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def __init__(self, open_size, close_size, average_size):
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WhiteEstimator.__init__(self, open_size, close_size, average_size)
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def _remove_particles(self, white):
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"""shows the image to a user so that he can visually check that the particles have been removed correctly in the given image
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"""
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raise NotImplementedError()
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# part_rem_settings_are_good = False
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# while part_rem_settings_are_good == False:
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# # perform opening to remove white particles
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# IJ.run( white_estimate, "Gray Morphology", "radius=1 type=square operator=open" )
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# # run("Gray Morphology", "radius=1 type=square operator=open");
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# # IJ.run( input_image_plus_copy, "Skeletonize (2D/3D)", "" )
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# # perform
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# if white_estimator_settings.particles_are_removed():
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# part_rem_settings_are_good = true
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# else
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# white_estimator_settings.ask
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def find_white_reference_image(white_estimate, white_z_stack):
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"""Find the white reference Image among a z stack of reference image the most correlated to the white image estimated from a serie of acquisition.
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:param IImage white_estimate:
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:param Sequence white_z_stack:
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:param IImageEngine image_engine: the image processor to use
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% this function is specific of Telemos images (DISCO line SOLEIL)
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% acquired using micromanager software linked to imageJ
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%% input
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% nothing : interactive function
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%% output
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% zmax : focal plane
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%% principe
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% images were acquired for a given roi which position is found in
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% metadata.txt file
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% white and dark images were recorded for the full field of view of the DISCO
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% TELEMOS camera
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%
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% correlation between a estimated white fluorescence image estalished from
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% actual acquisitions of a given sample and all z plane acquired for the reference TELEMOS white
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% image (Matthieu slide or any fluorescent homogeneous image) :
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% The estimated white fluorescence image is generallly obtained bt using function whiteFluoImageTelemosestimation
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% This is not compulsary as any homogenous sample image hat can roughly show the shape of illumination can be used to find
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% the white reference image
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%
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%
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% the z plane for which the maximum correlation is observed between estimated white and reference white images is retained.
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% the white image is then offsetted (its corresponding Dark is subtracted) and copied in the subfolder <WhiteReference> of the sample
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% rootfolder to show that it has been specifically selected for the considered experiment
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%The matlab corrcoeff function is used
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%
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% correlation coefficients are saved in a file called
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% 'corr.txt' in the subfolder 'WhiteReference'
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%
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%
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% expected input folder hierarchy:
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%
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% >sampleFolder
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% > PosFolders or RoiFolders
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% > WhiteEstimate
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% >darkFolder
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% >darkFolder.smooth
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% >whiteFolder
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% > darkFolderforWhite
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% > darkFolderforWhite.smooth
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% >whiteFolder.smooth
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%
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%
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% expected output folder hierarchy:
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% >sampleFolder
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% > PosFolders or RoiFolders
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% > WhiteEstimate
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% > WhiteReference
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% > white after offset
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% >darkFolder
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% >darkFolder.smooth
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% >whiteFolder
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% > darkFolderforWhite
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% > darkFolderforWhite.smooth
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% >whiteFolder.smooth
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%% use
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% [zmax]=findWhiteReferenceImageTelemos
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%% Comments
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% written for proposal 20161050
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% adapted for proposal 20170043
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%% Author
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% MF Devaux
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% INRA BIA
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% PVPP
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%% date
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% 5 octobre 2017:
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% 15 decembre 2017 : adapted to take into account the roi known from
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% metadata
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% 27 fevrier 2018 : comments details
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% 4 septembre 2018: comments and check and naming of folders
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% 12 mars 2019 : save white reference with the same size as white estimate
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% 16 avril 2019 : include diagonals to check the relevance of white
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% reference
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% 20 mai 2019 : track folder
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% 27 mai 2019 : offset dark
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% 4 juin 2019 : replace exist by isfolder or isfile
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"""
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raise NotImplementedError()
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def test_preprocessing(raw_images_root_path):
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"""Test preprocessing."""
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IImageEngine.set_instance(IJImageEngine())
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catalog = ImageCatalog(raw_images_root_path)
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sequence = catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
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white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
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white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
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# find_white_reference_image(white_estimate, sequence.get_white())
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print(white_estimate)
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IImageEngine.get_instance().save_as_tiff( white_estimate, './white_estimate.tiff' )
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print('end')
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if __name__ == '__main__':
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test_preprocessing()
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