more work related to graffy/lipase#3: for each pixel, the profile of variance along the circle is now computed. This image basically measures the non-roundedness for each pixel.
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Guillaume Raffy
parent
5a144f1907
commit
bfca19e039
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@ -1,8 +1,10 @@
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#@ ImagePlus (label="the input image") INPUT_IMAGE
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#@ Float (label="maximal radius", value=10.0, min=0.0, max=100.0, style="slider") MAX_RADIUS
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#@ Int (label="number of angular sectors", value=4, min=0, max=100, style="slider") NUM_ANGULAR_SECTORS
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#@ Float (label="maximal radius", value=32.0, min=0.0, max=100.0, style="slider") MAX_RADIUS
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#@ Integer (label="number of radial sectors", value=8, min=0, max=100, style="slider") NUM_RADIAL_SECTORS
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#@ Integer (label="number of angular sectors", value=4, min=0, max=100, style="slider") NUM_ANGULAR_SECTORS
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#@output ImagePlus RADIAL_PROFILE
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#@output ImagePlus RADIAL_PROFILES
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#@output ImagePlus ANGULAR_VARIANCE_AVG_IMAGE
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"""This script is supposed to be launched from fiji's jython interpreter
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This imagej plugin computes the radial profile of each pixel of the input image. The resulting profiles are stored in a single hyperstack, where the profile data are stored along the channel axis
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@ -25,17 +27,20 @@ from jarray import zeros, array # pylint: disable=import-error
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def run_script():
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global INPUT_IMAGE # pylint:disable=global-variable-not-assigned
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global MAX_RADIUS # pylint:disable=global-variable-not-assigned
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global RADIAL_PROFILE # pylint:disable=global-variable-not-assigned
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global NUM_RADIAL_SECTORS # pylint:disable=global-variable-not-assigned
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global NUM_ANGULAR_SECTORS # pylint:disable=global-variable-not-assigned
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global RADIAL_PROFILES # pylint:disable=global-variable-not-assigned
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global ANGULAR_VARIANCE_AVG_IMAGE # pylint:disable=global-variable-not-assigned
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IImageEngine.set_instance(IJImageEngine())
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src_image = IImageEngine.get_instance().create_image(width=1, height=1, pixel_type=PixelType.U8)
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src_image.ij_image = INPUT_IMAGE # pylint: disable=undefined-variable
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detector = CircularSymmetryDetector(max_radius=MAX_RADIUS, num_angular_sectors=NUM_ANGULAR_SECTORS) # pylint: disable=undefined-variable
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radial_profiles = detector.compute_radial_profiles(src_image)
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detector = CircularSymmetryDetector(max_radius=MAX_RADIUS, num_angular_sectors=NUM_ANGULAR_SECTORS, num_radial_sectors=NUM_RADIAL_SECTORS) # pylint: disable=undefined-variable
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radial_profiles, angular_variance_avg_image = detector.compute_radial_profiles(src_image)
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RADIAL_PROFILE = radial_profiles.hyperstack
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RADIAL_PROFILES = radial_profiles.hyperstack
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ANGULAR_VARIANCE_AVG_IMAGE = angular_variance_avg_image.ij_image
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# note : when launched from fiji, __name__ doesn't have the value "__main__", as when launched from python
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@ -168,12 +168,17 @@ class CircularSymmetryDetector:
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""" Computes for each pixel the radial profile (with this pixel as center)
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:param IImage src_image:
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:rtype IHyperstack: each radial profile is stored in the channel coordinate of the hyperstack
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:rtype IHyperstack, Image :
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:returns:
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- radial_profiles (:py:class:`IHyperstack`) - each radial profile is stored in the channel coordinate of the hyperstack
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- angular_variance_avg (:py:class:`IImage`) - each pixel stores the average variance of signal along the circles of different diameters in the neighborhood
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"""
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# https://stackoverflow.com/questions/39759503/how-to-document-multiple-return-values-using-restructuredtext-in-python-2
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ie = IImageEngine.get_instance()
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ie.debugger.on_image(src_image, 'src_image')
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projector_base = CircularSymmetryProjectorBase(self.max_radius, num_angular_sectors=self.num_angular_sectors, num_radial_sectors=self.num_radial_sectors, oversampling_scale=1)
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radial_profile_image = ie.create_hyperstack(width=src_image.get_width(), height=src_image.get_height(), num_channels=projector_base.num_radial_sectors, num_slices=1, num_frames=1, pixel_type=PixelType.F32)
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angular_variances_image = ie.create_hyperstack(width=src_image.get_width(), height=src_image.get_height(), num_channels=projector_base.num_radial_sectors, num_slices=1, num_frames=1, pixel_type=PixelType.F32)
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for radius_index in range(projector_base.num_radial_sectors):
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circle_stack = ie.create_hyperstack(width=src_image.get_width(), height=src_image.get_height(), num_channels=projector_base.num_angular_sectors, num_slices=1, num_frames=1, pixel_type=PixelType.F32)
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for angular_sector_index in range(projector_base.num_angular_sectors):
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@ -184,6 +189,15 @@ class CircularSymmetryDetector:
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circle_stack.set_image(projection, frame_index=0, slice_index=0, channel_index=angular_sector_index)
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# compute the image in which each pixel contains the mean value of the source image in the given circular region around the pixel
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circle_mean_image = ie.compute_mean(StackImageFeeder(circle_stack))
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radial_profile_image.set_image(circle_mean_image, frame_index=0, slice_index=0, channel_index=radius_index)
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return radial_profile_image
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square_diffs_stack = circle_stack # note : circle_stack is reused to store square_diffs_stack
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for angular_sector_index in range(projector_base.num_angular_sectors):
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angular_sector_image = circle_stack.get_image(frame_index=0, slice_index=0, channel_index=angular_sector_index)
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diff_image = ie.subtract(angular_sector_image, circle_mean_image)
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square_diff_image = ie.multiply(diff_image, diff_image)
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square_diffs_stack.set_image(square_diff_image, frame_index=0, slice_index=0, channel_index=angular_sector_index)
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variance_image = ie.compute_mean(StackImageFeeder(square_diffs_stack))
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angular_variances_image.set_image(variance_image, frame_index=0, slice_index=0, channel_index=radius_index)
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angular_variance_avg_image = ie.compute_mean(StackImageFeeder(angular_variances_image))
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return radial_profile_image, angular_variance_avg_image
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@ -170,7 +170,6 @@ class IImageFeeder(ABC):
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creates an hyperstack from this image feeder
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:rtype IHyperStack
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"""
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it = iter(self)
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image = it.next()
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@ -235,6 +234,9 @@ class StackImageFeeder(IImageFeeder):
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raise StopIteration
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else:
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image = self.hyperstack.get_image(frame_index=self.next_frame_index, slice_index=self.next_slice_index, channel_index=self.next_channel_index)
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# mean_value = image.get_mean_value()
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# print("mean_value", mean_value)
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# assert mean_value > 0.001
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# compute next image index
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self.next_slice_index += 1
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@ -381,6 +383,16 @@ class IImageEngine(ABC):
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:rtype IImage: image1-image2
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"""
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@abc.abstractmethod
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def multiply(self, image1, image2):
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"""
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computes the difference image1-image2
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:param IImage image1:
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:param IImage image2:
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:rtype IImage: image1*image2
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"""
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@abc.abstractmethod
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def divide(self, numerator_image, denominator_image):
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"""
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@ -290,6 +290,11 @@ class IJImageEngine(IImageEngine):
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result_image = ic.run("Subtract create float", image1.ij_image, image2.ij_image)
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return IJImage(self, result_image)
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def multiply(self, image1, image2):
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ic = ImageCalculator()
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result_image = ic.run("Multiply create float", image1.ij_image, image2.ij_image)
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return IJImage(self, result_image)
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def divide(self, numerator_image, denominator_image):
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ic = ImageCalculator()
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result_image = ic.run("Divide create float", numerator_image.ij_image, denominator_image.ij_image)
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