Image

Description

A gnomon Image is a data strucure which could hold time series image in one channel or multi-channel (4D data set).
The corresponding class in gnomon is gnomonImageDataMultiChannelImage.
It gives possibility to access some information about image like:

• Number of channels

• Dimensions

• Voxel Type

• Voxel Size

Default reader plugin

The default reader of image form is imageReaderTimagetk. Which reads a 3D microscopy intensity image file.
Extensions supported by this reader are: inr, inr.gz, mha, .mha.gz, tif, tiff, czi, lsm.

Default writer plugin

The default writer of image form is gnomonImageWriter

Gnomon Image Example

Plugins which take Image as input

Here is a non exhaustive list of some algorithms which take this form as input.

• boundaryEdgeEnhancement

• linearFilterTimagetk

• binarization

• lsmCellsSegmentation

Plugins which produce Image as output

Here is a non exhaustive list of some algorithms which produce this form as output.

• anisotropic3dImageEnhancement

• edgeIndicatorLSM3d

• linearFilterTimagetk

• registrationTimagetk

A Use Case, Resampling an image

from copy import deepcopy
import numpy as np

from dtkcore import d_real

import gnomon.core
from gnomon.utils import algorithmPlugin
from gnomon.utils.decorators import imageInput, imageOutput

from timagetk.algorithms.resample import isometric_resampling


@algorithmPlugin(version='0.3.1', coreversion='0.81.1')
@imageInput(attr='in_img', data_plugin='gnomonImageDataMultiChannelImage')
@imageOutput(attr='out_img', data_plugin='gnomonImageDataMultiChannelImage')
class isometricResampling(gnomon.core.gnomonAbstractFormAlgorithm):

    def __init__(self):
        super().__init__()

        self._parameters = {}
        self._parameters['voxelsize'] = d_real("Voxelsize", 1., 0.1, 5., 2, "Target voxelsize after resampling")

        self.in_img = {}
        self.out_img = {}

    def run(self):
        self.out_img = {}

        for time in self.in_img.keys():
            resampled_img = isometric_resampling(deepcopy(self.in_img[time]), method=self['voxelsize'])
            self.out_img[time] = resampled_img