diff --git a/documentation/release_5.2.htm b/documentation/release_5.2.htm index 3f06a7bd1a..8314e859cf 100644 --- a/documentation/release_5.2.htm +++ b/documentation/release_5.2.htm @@ -127,7 +127,10 @@

Changed functionality


PR #1243.
  • The Succeeded class has a new method bool succeeded() enabling more concise code (avoiding the need for comparing with Succeeded::yes which is especially verbose in Python). -
    • + +
  • The example files for the Siemens mMR now use lower min/max thresholds for the (single) scatter scale. This gives better results, see Issue #1163. +
    PR #1279. +

    • Deprecated functionality

    diff --git a/examples/Siemens-mMR/scatter_and_recon.sh b/examples/Siemens-mMR/scatter_and_recon.sh index 9442840da0..fa45238f3e 100755 --- a/examples/Siemens-mMR/scatter_and_recon.sh +++ b/examples/Siemens-mMR/scatter_and_recon.sh @@ -75,7 +75,7 @@ echo "Estimating scatter (be patient). Log saved in output/scatter.log" # filename-prefix for additive sino (i.e. "precorrected" sum of scatter and randoms) total_additive_prefix=output/total_additive num_scat_iters=3 -scatter_pardir=${pardir}/../samples/scatter_estimation_par_files +scatter_pardir=${pardir}/scatter_estimation_par_files # you might have to change this for a different scanner than the mMR scatter_recon_num_subiterations=21 scatter_recon_num_subsets=21 diff --git a/examples/Siemens-mMR/scatter_estimation_par_files/README.md b/examples/Siemens-mMR/scatter_estimation_par_files/README.md new file mode 100644 index 0000000000..1bd540f3b0 --- /dev/null +++ b/examples/Siemens-mMR/scatter_estimation_par_files/README.md @@ -0,0 +1,19 @@ +# Example files for running scatter estimation for the Siemens mMR + +Files made by Nikos Efthimou and fine-tuned by Kris Thielemans.
    +Copyright University of Hull 2018-2019
    +copyright University College London 2016, 2020
    +Distributed under the Apache 2.0 License + +These files are almost identical to those in +[examples/samples/scatter_estimation_par_files/](../../samples/scatter_estimation_par_files/README.md), +see there for some more information. + +Currently the only difference are the lower values for +``` +maximum scatter scaling factor := .5 +minimum scatter scaling factor := 0.1 +``` + +These have been shown to work better for mMR data, see e.g. +[STIR issue #1163](https://github.com/UCL/STIR/issues/1163). diff --git a/examples/Siemens-mMR/scatter_estimation_par_files/postfilter_Gaussian_for_mask.par b/examples/Siemens-mMR/scatter_estimation_par_files/postfilter_Gaussian_for_mask.par new file mode 100644 index 0000000000..d6af00a358 --- /dev/null +++ b/examples/Siemens-mMR/scatter_estimation_par_files/postfilter_Gaussian_for_mask.par @@ -0,0 +1,12 @@ +PostFilteringParameters := + Postfilter type := Separable Gaussian +Separable Gaussian Filter Parameters := +x-dir filter FWHM (in mm):= 20 +y-dir filter FWHM (in mm):= 20 +z-dir filter FWHM (in mm):= 15 +; optionally restrict kernel sizes +; x-dir maximum kernel size := 129 +; y-dir maximum kernel size := 129 +; z-dir maximum kernel size := 31 +END Separable Gaussian Filter Parameters := +End PostFiltering Parameters:= diff --git a/examples/Siemens-mMR/scatter_estimation_par_files/run_reconstruction.par b/examples/Siemens-mMR/scatter_estimation_par_files/run_reconstruction.par new file mode 100644 index 0000000000..166bdff2e1 --- /dev/null +++ b/examples/Siemens-mMR/scatter_estimation_par_files/run_reconstruction.par @@ -0,0 +1,44 @@ +Reconstruction Parameters := +reconstruction type := OSMAPOSL +OSMAPOSLParameters := + +objective function type:= PoissonLogLikelihoodWithLinearModelForMeanAndProjData +PoissonLogLikelihoodWithLinearModelForMeanAndProjData Parameters:= +maximum absolute segment number to process := -1 + +projector pair type := Matrix + Projector Pair Using Matrix Parameters := + Matrix type := Ray Tracing + Ray tracing matrix parameters := + number of rays in tangential direction to trace for each bin:= 5 + End Ray tracing matrix parameters := + End Projector Pair Using Matrix Parameters := + +;recompute sensitivity := 0 +;subset sensitivity filenames := scatter_subset_sens_%d.hv + +; reconstruct at large voxel size to save time +zoom := 0.2 + +end PoissonLogLikelihoodWithLinearModelForMeanAndProjData Parameters:= + +; initial estimate := +enforce initial positivity condition:=1 + +number of subsets:= ${scatter_recon_num_subsets} +number of subiterations:=${scatter_recon_num_subiterations} +;save estimates at subiteration intervals:= ${scatter_recon_num_subiterations} + +; smooth a bit as we use a down-sampled scanner (during the scatter estimation resolution can be low) +post-filter type := Separable Gaussian +Separable Gaussian Filter Parameters := + x-dir filter FWHM (in mm):= 15 + y-dir filter FWHM (in mm):= 15 + z-dir filter FWHM (in mm):= 15 +END Separable Gaussian Filter Parameters := +; +; Disable output +; +disable output := 1 +End OSMAPOSLParameters:= +End reconstruction Parameters:= diff --git a/examples/Siemens-mMR/scatter_estimation_par_files/scatter_estimation.par b/examples/Siemens-mMR/scatter_estimation_par_files/scatter_estimation.par new file mode 100644 index 0000000000..771f0daf85 --- /dev/null +++ b/examples/Siemens-mMR/scatter_estimation_par_files/scatter_estimation.par @@ -0,0 +1,86 @@ +Scatter Estimation Parameters := + +;Run in debug mode +;; A new folder called extras will be created, in which many +;; extra files will be stored +run in debug mode := 1 + +; Measured data +input file := ${sino_input} + +; Attenuation Image +attenuation image filename := ${atnimg} + +; Normalisation coefficients & attenuation data +Normalisation type := from ProjData + Bin Normalisation From ProjData := + normalisation projdata filename:= ${NORM} + End Bin Normalisation From ProjData:= + +attenuation correction factors filename := ${acf3d} + +;; Background data (not normalised). +; Should be set to the randoms estimate (unless you precorrected, but we haven't tested that) +background projdata filename := ${randoms3d} + +; Mask for tail-fitting +; It will be computed by masking the attenuation image, and forward projecting that. +; If !recompute mask projdata then the filename must be set. +recompute mask projdata := 1 +mask projdata filename := ${mask_projdata_filename} + +; Input or output filename - depends on recompute +recompute mask image := 1 +mask image filename := ${mask_image} +; threshold to be applied after filtering (in cm^-1). Default value is below +mask attenuation image min threshold := 0.003 +; optional filename to specify a filter before thresholding the attenuation image +; By default a Gaussian filter with FWHM (15,20,20) will be used. Here we use an explicit file as an example. +mask attenuation image filter filename := ${scatter_pardir}/postfilter_Gaussian_for_mask.par +;End of Mask + +;Parameter file for the tail fitting of the scatter data (within the mask) +tail fitting parameter filename := ${scatter_pardir}/tail_fitting.par + +; Run simulation and reconstruction in 2D and export SSRB sinograms (currently required) +run in 2d projdata := 1 + +; ScatterSimulation parameters +; could read from a file, but instead we have them below +; scatter simulation parameter filename := ${scatter_pardir}/scatter_simulation.par +Scatter Simulation type := PET Single Scatter Simulation + PET Single Scatter Simulation Parameters := + ; could change some parameters here if you need to (not recommended) + End PET Single Scatter Simulation Parameters:= + +; next option is the default +use scanner downsampling in scatter simulation := 1 + +; could add parameters below, but reading it from file +; reconstruction type := ... +reconstruction parameter filename := ${scatter_pardir}/run_reconstruction.par + +; +; This is the number of times which the Scatter Estimation will +; iterate. Default is 5 + +number of scatter iterations := ${num_scat_iters} + +; Average the first two activity images +do average at 2 := 1 + +; Export scatter estimates of each iteration +export scatter estimates of each iteration := 1 + +output scatter estimate name prefix := ${scatter_prefix} +output additive estimate name prefix:= ${total_additive_prefix} + +maximum scatter scaling factor := 0.4 +minimum scatter scaling factor := 0.1 + +;Upsample and fit +; defaults to 3. +upsampling half filter width := 3 +remove interleaving before upsampling := 1 + +End Scatter Estimation Parameters := diff --git a/examples/Siemens-mMR/scatter_estimation_par_files/tail_fitting.par b/examples/Siemens-mMR/scatter_estimation_par_files/tail_fitting.par new file mode 100644 index 0000000000..dc0d1459f4 --- /dev/null +++ b/examples/Siemens-mMR/scatter_estimation_par_files/tail_fitting.par @@ -0,0 +1,4 @@ +CreateTailMaskFromACFs := + ACF-threshold := 1.1 + safety-margin := 4 +END CreateTailMaskFromACFs :=