Filters¶
Filters transform data and have at least one input and one output.
Point-based transformation¶
Binarization¶
Clipping¶
Arithmetic expressions¶
-
class
calculate
¶ Calculate an arithmetic expression. You have access to the value stored in the input buffer via the v letter in
expression
and to the index of v via letter x. Please be aware that v is a floating point number while x is an integer. This is useful if you have multidimensional data and want to address only one dimension. Let’s say the input is two dimensional, 256 pixels wide and you want to fill the x-coordinate with x for all respective y-coordinates (a gradient in x-direction). Then you can write expression=”x % 256”. Another example is the sinc function which you would calculate as expression=”sin(v) / x” for 1D input. For more complex math or other operations please consider using OpenCL.-
"expression"
: string¶ Arithmetic expression with math functions supported by OpenCL.
-
Statistics¶
Generic OpenCL¶
-
class
opencl
¶ Load an arbitrary
kernel
fromfilename
orsource
and execute it on each input. The kernel must accept as many global float array parameters as connected to the filter and one additional as an output.-
"filename"
: string¶ Filename with kernel sources to load.
-
"source"
: string¶ String with OpenCL kernel code.
-
"kernel"
: string¶ Name of the kernel that this filter is associated with.
-
"dimensions"
: uint¶ Number of dimensions the kernel works on. Must be in [1, 3].
-
Spatial transformation¶
Flipping¶
Binning¶
Rescaling¶
-
class
rescale
¶ Rescale input data by a fixed
factor
.-
"factor"
: float¶ Fixed factor for scaling the input in both directions.
-
"x-factor"
: float¶ Fixed factor for scaling the input width.
-
"y-factor"
: float¶ Fixed factor for scaling the input height.
-
"width"
: uint¶ Fixed width, disabling scalar rescaling.
-
"height"
: uint¶ Fixed height, disabling scalar rescaling.
-
"interpolation"
: enum¶ Interpolation method used for rescaling which can be either
nearest
orlinear
.
-
Padding¶
-
class
pad
¶ Pad an image to some extent with specific behavior for pixels falling outside the original image.
-
"x"
: int¶ Horizontal coordinate in the output image which will contain the first input column.
-
"y"
: int¶ Vertical coordinate in the output image which will contain the first input row.
-
"width"
: uint¶ Width of the padded image.
-
"height"
: uint¶ Height of the padded image.
-
"addressing-mode"
: enum¶ Addressing mode specifies the behavior for pixels falling outside the original image. See OpenCL
sampler_t
documentation for more information.
-
Cropping¶
-
class
crop
¶ Crop a region of interest from two-dimensional input. If the region is (partially) outside the input, only accessible data will be copied.
-
"x"
: uint¶ Horizontal coordinate from where to start the ROI.
-
"y"
: uint¶ Vertical coordinate from where to start the ROI.
-
"width"
: uint¶ Width of the region of interest.
-
"height"
: uint¶ Height of the region of interest.
-
"from-center"
: boolean¶ Start cropping from the center outwards.
-
Polar transformation¶
-
class
polar-coordinates
¶ Transformation between polar and cartesian coordinate systems.
When transforming from cartesian to polar coordinates the origin is in the image center (
width
/ 2,height
/ 2). When transforming from polar to cartesian coordinates the origin is in the image corner (0, 0).-
"width"
: uint¶ Final width after transformation.
-
"height"
: uint¶ Final height after transformation.
-
"direction"
: string¶ Conversion direction from
polar_to_cartesian
.
-
Multi-stream¶
Interpolation¶
-
class
interpolate
¶ Interpolates incoming data from two compatible streams, i.e. the task computes \((1 - \alpha) s_1 + \alpha s_2\) where \(s_1\) and \(s_2\) are the two input streams and \(\alpha\) a blend factor. \(\alpha\) is \(i / (n - 1)\) for \(n > 1\), \(n\) being
number
and \(i\) the current iteration.-
"number"
: uint¶ Number of total input stream length.
-
Subtract¶
-
class
subtract
Subtract data items of the second from the first stream.
Stream transformations¶
Averaging¶
Statistics¶
Stacking¶
Merging¶
Slice mapping¶
-
class
map-slice
¶ Lays out input images on a quadratic grid. If the
number
of input elements is not the square of some integer value, the next higher number is chosen and the remaining data is blackened.-
"number"
: uint¶ Number of expected input elements. If more elements are sent to the mapper, warnings are issued.
-
Fourier domain¶
Fast Fourier transform¶
-
class
fft
¶ Compute the Fourier spectrum of input data. If
dimensions
is one but the input data is 2-dimensional, the 1-D FFT is computed for each row.-
"auto-zeropadding"
: boolean¶ Automatically zeropad input data to a size to the next power of 2.
-
"dimensions"
: uint¶ Number of dimensions in [1, 3].
-
"size-x"
: uint¶ Size of FFT transform in x-direction.
-
"size-y"
: uint¶ Size of FFT transform in y-direction.
-
"size-z"
: uint¶ Size of FFT transform in z-direction.
-
-
class
ifft
¶ Compute the inverse Fourier of spectral input data. If
dimensions
is one but the input data is 2-dimensional, the 1-D FFT is computed for each row.-
"dimensions"
: uint¶ Number of dimensions in [1, 3].
-
"crop-width"
: int¶ Width to crop output.
-
"crop-height"
: int¶ Height to crop output.
-
Frequency filtering¶
-
class
filter
¶ Computes a frequency filter function and multiplies it with its input, effectively attenuating certain frequencies.
-
"filter "
: enum¶ Any of
ramp
,ramp-fromreal
,butterworth
,faris-byer
andhamming
. The default filter isramp-fromreal
which computes a correct ramp filter avoiding offset issues encountered with naive implementations.
-
"scale"
: float¶ Arbitrary scale that is multiplied to each frequency component.
-
"cutoff"
: float¶ Cutoff frequency of the Butterworth filter.
-
"order"
: float¶ Order of the Butterworth filter.
-
"tau"
: float¶ Tau parameter of Faris-Byer filter.
-
"theta"
: float¶ Theta parameter of Faris-Byer filter.
-
1D stripe filtering¶
-
class
filter-stripes1d
¶ Filter stripes in 1D along the x-axis. The input and output are in frequency domain. The filter multiplies the frequencies with an inverse Gaussian profile centered at 0 frequency. The inversed profile means that the filter is f(k) = 1 - gauss(k) in order to suppress the low frequencies.
-
"strength"
: float¶ Filter strength, which is the full width at half maximum of the gaussian.
-
Zeropadding¶
-
class
zeropad
¶ Add zeros in the center of sinogram using
oversampling
to manage the amount of zeros which will be added.-
"oversampling"
: uint¶ Oversampling coefficient.
-
"center-of-rotation"
: float¶ Center of rotation of sample.
-
Reconstruction¶
Flat-field correction¶
-
class
flat-field-correct
¶ Computes the flat field correction using three data streams:
- Projection data on input 0
- Dark field data on input 1
- Flat field data on input 2
-
"absorption-correct"
: boolean¶ If TRUE, compute the negative natural logarithm of the flat-corrected data.
-
"fix-nan-and-inf"
: boolean¶ If TRUE, replace all resulting NANs and INFs with zeros.
-
"sinogram-input"
: boolean¶ If TRUE, correct only one line (the sinogram), thus darks are flats are 1D.
-
"dark-scale"
: float¶ Scale the dark field prior to the flat field correct.
Sinogram transposition¶
-
class
transpose-projections
¶ Read a stream of two-dimensional projections and output a stream of transposed sinograms.
number
must be set to the number of incoming projections to allocate enough memory.-
"number"
: uint¶ Number of projections.
Warning
This is a memory intensive task and can easily exhaust your system memory. Make sure you have enough memory, otherwise the process will be killed.
-
Tomographic backprojection¶
-
class
backproject
¶ Computes the backprojection for a single sinogram.
-
"num-projections"
: uint¶ Number of projections between 0 and 180 degrees.
-
"offset"
: uint¶ Offset to the first projection.
-
"axis-pos"
: double¶ Position of the rotation axis in horizontal pixel dimension of a sinogram or projection. If not given, the center of the sinogram is assumed.
-
"angle-step"
: double¶ Angle step increment in radians. If not given, pi divided by height of input sinogram is assumed.
-
"angle-offset"
: double¶ Constant angle offset in radians. This determines effectively the starting angle.
-
"mode"
: enum¶ Reconstruction mode which can be either
nearest
ortexture
.
-
"roi-x"
: uint¶ Horizontal coordinate of the start of the ROI. By default 0.
-
"roi-y"
: uint¶ Vertical coordinate of the start of the ROI. By default 0.
-
"roi-width"
: uint¶ Width of the region of interest. The default value of 0 denotes full width.
-
"roi-height"
: uint¶ Height of the region of interest. The default value of 0 denotes full height.
-
Forward projection¶
Laminographic backprojection¶
-
class
lamino-backproject
¶ Backprojects parallel beam computed laminography projection-by-projection into a 3D volume.
-
"region-values"
: int¶ Elements in regions.
-
"float-region-values"
: float¶ Elements in float regions.
-
"x-region"
: GValueArray¶ X region for reconstruction as (from, to, step).
-
"y-region"
: GValueArray¶ Y region for reconstruction as (from, to, step).
-
"z"
: float¶ Z coordinate of the reconstructed slice.
-
"region"
: GValueArray¶ Region for the parameter along z-axis as (from, to, step).
-
"projection-offset"
: GValueArray¶ Offset to projection data as (x, y) for the case input data is cropped to the necessary range of interest.
-
"center"
: GValueArray¶ Center of the volume with respect to projections (x, y), (rotation axes).
-
"overall-angle"
: float¶ Angle covered by all projections (can be negative for negative steps in case only num-projections is specified)
-
"num-projections"
: uint¶ Number of projections.
-
"tomo-angle"
: float¶ Tomographic rotation angle in radians (used for acquiring projections).
-
"lamino-angle"
: float¶ Absolute laminogrpahic angle in radians determining the sample tilt.
-
"roll-angle"
: float¶ Sample angular misalignment to the side (roll) in radians (CW is positive).
-
"parameter"
: enum¶ Which paramter will be varied along the z-axis, from
z
,x-center
,lamino-angle
,roll-angle
.
-
Fourier interpolation¶
-
class
dfi-sinc
¶ Computes the 2D Fourier spectrum of reconstructed image using 1D Fourier projection of sinogram (fft filter must be applied before). There are no default values for properties, therefore they should be assigned manually.
-
"kernel-size"
: uint¶ The length of kernel which will be used in interpolation.
-
"number-presampled-values"
: uint¶ Number of presampled values which will be used to calculate
kernel-size
kernel coefficients.
-
"roi-size"
: int¶ The length of one side of region of Interest.
-
"angle-step"
: double¶ Increment of angle in radians.
-
Center of rotation¶
Sinogram offset shift¶
Phase retrieval¶
-
class
retrieve-phase
¶ Computes and applies a fourier filter to correct phase-shifted data. Expects frequencies as an input and produces frequencies as an output.
-
"method"
: enum¶ Retrieval method which is one of
tie
,ctf
,ctfhalfsine
,qp
,qphalfsine
orqp2
.
-
"energy"
: float¶ Energy in keV.
-
"distance"
: float¶ Distance in meter.
-
"pixel-size"
: float¶ Pixel size in meter.
-
"regularization-rate"
: float¶ Regularization parameter is log10 of the constant to be added to the denominator to regularize the singularity at zero frequency: 1/sin(x) -> 1/(sin(x)+10^-RegPar).
Typical values [2, 3].
-
"thresholding-rate"
: float¶ Parameter for Quasiparticle phase retrieval which defines the width of the rings to be cropped around the zero crossing of the CTF denominator in Fourier space.
Typical values in [0.01, 0.1],
qp
retrieval is rather independent of cropping width.
-
General matrix-matrix multiplication¶
-
class
gemm
¶ Computes \(\alpha A \cdot B + \beta C\) where \(A\), \(B\) and \(C\) are input streams 0, 1 and 2 respectively. \(A\) must be of size \(m\times k\), \(B\) \(k\times n\) and \(C\) \(m\times n\).
Note
This filter is only available if CLBlast support is available.
-
"alpha"
: float¶ Scalar multiplied with \(AB\).
-
"beta"
: float¶ Scalar multiplied with \(C\).
-
Segmentation¶
-
class
segment
¶ Segments a stack of images given a field of labels using the random walk algorithm described in [1]. The first input stream must contain three-dimensional image stacks, the second input stream a label image with the same width and height as the images. Any pixel value other than zero is treated as a label and used to determine segments in all directions.
[1] Lösel and Heuveline, Enhancing a Diffusion Algorithm for 4D Image Segmentation Using Local Information in Proc. SPIE 9784, Medical Imaging 2016, http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=2506235