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Add Deconvolution example
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‎docs/ops/doc/examples/deconvolution.rst‎

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=============
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Deconvolution
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=============
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In this example we will use SciJava Ops to perform Richardson-Lucy (RL) deconvolution on a 3D dataset (X, Y, Z) of
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a HeLa cell nucleus stained with DAPI (4′,6-diamidino-2-phenylindole) and imaged on an epifluorescent microscope at 100x.
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The SciJava Ops framework currently supports the standard RL algorithm as well as the Richardson-Lucy Total Variation (RLTV)
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algorithm, which utilizes a regularization factor to limit the noise amplified by the RL algorithm :sup:`1`.
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You can download the 3D HeLa cell nuclus data `here`_.
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The table below contains the necessary parameter values needed for the ``kernelDiffraction`` Op to create the synthetic
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point spread function (PSF) using the Gibson-Lanni model :sup:`2`.
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+--------------------------------------+-------+
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| Parameter | Value |
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+======================================+=======+
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| Iterations | 15 |
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+--------------------------------------+-------+
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| Numerical aperature | 1.45 |
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+--------------------------------------+-------+
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| Emission wavelength (nm) | 457 |
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+--------------------------------------+-------+
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| Refractive index (Immersion) | 1.5 |
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+--------------------------------------+-------+
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| Refractive index (Sample) | 1.4 |
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+--------------------------------------+-------+
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| Lateral resolution (μm/pixel) | 0.065 |
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+--------------------------------------+-------+
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| Axial resolution (μm/pixel) | 0.1 |
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+--------------------------------------+-------+
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| Particle/sample position (μm/pixel) | 0.0 |
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+--------------------------------------+-------+
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| Regularization factor | 0.002 |
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+--------------------------------------+-------+
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.. tabs::
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.. code-tab:: scijava-groovy
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#@ OpEnvironment ops
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#@ ImgPlus img
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#@ Integer iterations(label="Iterations", value=30)
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#@ Float numericalAperture(label="Numerical Aperture", style="format:0.00", min=0.00, value=1.45)
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#@ Integer wavelength(label="Emission Wavelength (nm)", value=550)
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#@ Float riImmersion(label="Refractive Index (immersion)", style="format:0.00", min=0.00, value=1.5)
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#@ Float riSample(label="Refractive Index (sample)", style="format:0.00", min=0.00, value=1.4)
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#@ Float lateral_res(label="Lateral resolution (μm/pixel)", style="format:0.0000", min=0.0000, value=0.065)
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#@ Float axial_res(label="Axial resolution (μm/pixel)", style="format:0.0000", min=0.0000, value=0.1)
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#@ Float pZ(label="Particle/sample Position (μm)", style="format:0.0000", min=0.0000, value=0)
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#@ Float regularizationFactor(label="Regularization factor", style="format:0.00000", min=0.00000, value=0.002)
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#@output ImgPlus psf
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#@output ImgPlus result
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import net.imglib2.FinalDimensions
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import net.imglib2.type.numeric.real.FloatType
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import net.imglib2.type.numeric.complex.ComplexFloatType
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// convert input image to float
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img_float = ops.op("create.img").arity2().input(img, new FloatType()).apply()
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ops.op("convert.float32").arity1().input(img).output(img_float).compute()
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// use image dimensions for PSF size
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psf_size = new FinalDimensions(img.dimensionsAsLongArray())
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// convert the input parameters to meters (m)
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wavelength = wavelength.toFloat() * 1E-9
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lateral_res = lateral_res * 1E-6
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axial_res = axial_res * 1E-6
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pZ = pZ * 1E-6
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// create the synthetic PSF
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psf = ops.op("create.kernelDiffraction").arity9().input(psf_size,
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numericalAperture,
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wavelength,
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riSample,
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riImmersion,
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lateral_res,
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axial_res,
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pZ,
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new FloatType()).apply()
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// deconvole image
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result = ops.op("deconvolve.richardsonLucyTV").arity8().input(img_float, psf, new FloatType(), new ComplexFloatType(), iterations, false, false, regularizationFactor).apply()
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.. code-tab:: python
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#@ OpEnvironment ops
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#@ ImgPlus img
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#@ Integer iterations(label="Iterations", value=30)
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#@ Float numericalAperture(label="Numerical Aperture", style="format:0.00", min=0.00, value=1.45)
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#@ Integer wavelength(label="Emission Wavelength (nm)", value=550)
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#@ Float riImmersion(label="Refractive Index (immersion)", style="format:0.00", min=0.00, value=1.5)
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#@ Float riSample(label="Refractive Index (sample)", style="format:0.00", min=0.00, value=1.4)
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#@ Float lateral_res(label="Lateral resolution (μm/pixel)", style="format:0.0000", min=0.0000, value=0.065)
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#@ Float axial_res(label="Axial resolution (μm/pixel)", style="format:0.0000", min=0.0000, value=0.1)
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#@ Float pZ(label="Particle/sample Position (μm)", style="format:0.0000", min=0.0000, value=0)
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#@ Float regularizationFactor(label="Regularization factor", style="format:0.00000", min=0.00000, value=0.002)
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#@output ImgPlus psf
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#@output ImgPlus result
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from net.imglib2 import FinalDimensions
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from net.imglib2.type.numeric.real import FloatType
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from net.imglib2.type.numeric.complex import ComplexFloatType
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# convert input image to float
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img_float = ops.op("create.img").arity2().input(img, FloatType()).apply()
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ops.op("convert.float32").arity1().input(img).output(img_float).compute()
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# use image dimensions for PSF size
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psf_size = FinalDimensions(img.dimensionsAsLongArray())
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# convert the input parameters to meters (m)
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wavelength = float(wavelength) * 1E-9
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lateral_res = lateral_res * 1E-6
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axial_res = axial_res * 1E-6
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pZ = pZ * 1E-6
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# create the synthetic PSF
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psf = ops.op("create.kernelDiffraction").arity9().input(psf_size,
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numericalAperture,
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wavelength,
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riSample,
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riImmersion,
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lateral_res,
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axial_res,
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pZ,
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FloatType()).apply()
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# deconvole image
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result = ops.op("deconvolve.richardsonLucyTV").arity8().input(img_float, psf, FloatType(), ComplexFloatType(), iterations, False, False, regularizationFactor).apply()
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| :sup:`1`: `Dey et. al, Micros Res Tech 2006`_
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| :sup:`2`: `Gibson & Lanni, JOSA 1992`_
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.. _`Dey et. al, Micros Res Tech 2006`: https://pubmed.ncbi.nlm.nih.gov/16586486/
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.. _`Gibson & Lanni, JOSA 1992`: https://pubmed.ncbi.nlm.nih.gov/1738047/
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.. _`here`: https://media.imagej.net/sample_data/3d/hela_nucleus.tif

‎docs/ops/doc/index.rst‎

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:maxdepth: 2
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:caption: ⚙️ Examples
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examples/deconvolution
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examples/example_gaussian_subtraction
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examples/opencv_denoise
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