Merge pull request #161 from MagneticResonanceImaging/nh/regLSUpdate

Update RegLS interface

MRIFiles/test/runtests.jl

@@ -1,5 +1,5 @@
 using Test, LinearAlgebra, MRIFiles, MRIReco, MRICoilSensitivities
-
+using MRIReco.RegularizedLeastSquares
 using Scratch
 using LazyArtifacts
 using ImageUtils

MRIFiles/test/testBrukerFile.jl

@@ -98,9 +98,8 @@ params = Dict{Symbol, Any}()
 params[:reco] = "multiCoil"    # encoding model
 params[:reconSize] = acq.encodingSize
 params[:sparseTrafo] = "Wavelet" #sparse trafo
-params[:regularization] = "L1"       # regularization
-params[:λ] = 30.0
-params[:solver] = "admm"    # solver
+params[:reg] = L1Regularization(30.0)       # regularization
+params[:solver] = ADMM    # solver
 params[:iterations] = 3
 params[:iterationsInner] = 2
 params[:ρ] = 1.0e-1

Project.toml

@@ -1,7 +1,7 @@
 name = "MRIReco"
 uuid = "bdf86e05-2d2b-5731-a332-f3fe1f9e047f"
 authors = ["Tobias Knopp <[email protected]>"]
-version = "0.8.0"
+version = "0.9.0"
 
 [deps]
 AxisArrays = "39de3d68-74b9-583c-8d2d-e117c070f3a9"
@@ -26,7 +26,7 @@ MRIOperators = "0.2"
 PrecompileTools = "1"
 ProgressMeter = "1.2"
 Reexport = "0.2, 1"
-RegularizedLeastSquares = "0.9.0, 0.10"
+RegularizedLeastSquares = "0.11"
 Unitful = "1.2"
 julia = "1.6"
 

docs/lit/examples/03-subspaceReconstruction.jl

@@ -12,6 +12,7 @@ using ImageUtils: shepp_logan
 using LinearAlgebra
 using  Random
 using MRIReco, MRISimulation, MRICoilSensitivities, MRISampling,MRIOperators
+using MRIReco.RegularizedLeastSquares
 color=Makie.wong_colors() # color for plots
 
 N = 128
@@ -86,10 +87,9 @@ acqData_u2 = AcquisitionData(kspace);
 params = Dict{Symbol,Any}()
 params[:reconSize] = (N, N)
 params[:reco] = "multiCoilMultiEcho"
-params[:regularization] = "L2"
-params[:λ] = 1.e-3
+params[:reg] = L2Regularization(1.e-3)
 params[:iterations] = 1
-params[:solver] = "cgnr"
+params[:solver] = CGNR
 params[:senseMaps] = reshape(coilsens, N, N, 1, nCh)
 
 im_x = reconstruction(acqData, params).data # fully reconstruction
@@ -192,10 +192,9 @@ params = Dict{Symbol,Any}()
 params[:reconSize] = (N, N)
 params[:reco] = "multiCoilMultiEchoSubspace"
 
-params[:regularization] = "L1"
+params[:reg] = L1Regularization(0.001)
 params[:sparseTrafo] = "Wavelet" #sparse trafo
-params[:λ] = 0.001
-params[:solver] = "admm"
+params[:solver] = ADMM
 params[:senseMaps] = reshape(coilsens, N, N, 1, nCh)
 params[:basis] = basis
 

docs/src/SENSE.md

@@ -32,10 +32,9 @@ acqData = simulation(I, params)
 params = Dict{Symbol, Any}()
 params[:reco] = "multiCoil"
 params[:reconSize] = (N,N)
-params[:regularization] = "L2"
-params[:λ] = 1.e-3
+params[:reg] = L2Regularization(1.e-3)
 params[:iterations] = 40
-params[:solver] = "cgnr"
+params[:solver] = CGNR
 params[:senseMaps] = coilsens
 
 # do reconstruction

docs/src/compressedSensing.md

@@ -52,11 +52,10 @@ params[:reco] = "multiCoil"
 params[:reconSize] = (320,320)
 params[:senseMaps] = smaps
 
-params[:solver] = "cgnr"
-params[:regularization] = "L2"
-params[:λ] = 1.e-4
+params[:solver] = CGNR
+params[:reg] = L2Regularization(1.e-4)
 params[:iterations] = 5
-params[:normalizeReg] = true
+params[:normalizeReg] = MeasurementBasedNormalization()
 
 img_cg = reconstruction(acqDataSub, params)
 ```
@@ -69,15 +68,14 @@ params[:reco] = "multiCoil"
 params[:reconSize] = (320,320)
 params[:senseMaps] = smaps
 
-params[:solver] = "admm"
-params[:regularization] = "TV"
-params[:λ] = 1.e-1 # 5.e-2
+params[:solver] = ADMM
+params[:reg] = TVRegularization(1.e-1, shape = (320, 320))
 params[:iterations] = 50
 params[:ρ] = 0.1
 params[:absTol] = 1.e-4
 params[:relTol] = 1.e-2
 params[:tolInner] = 1.e-2
-params[:normalizeReg] = true
+params[:normalizeReg] = MeasurementBasedNormalization()
 
 img_tv = reconstruction(acqDataSub, params)
 ```

docs/src/custom.md

@@ -85,11 +85,10 @@ params = Dict{Symbol,Any}()
 params[:reco] = "standard"
 params[:reconSize] = (nx,ny)
 params[:iterations] = 50
-params[:λ] = 2.e-2
-params[:regularization] = "L1"
+params[:reg] = L1Regularization(2.e-2)
 params[:sparseTrafo] = dictOp(D,(nx,ny),(px,py),2.e-2)
 params[:ρ] = 0.1
-params[:solver] = "admm"
+params[:solver] = ADMM
 params[:absTol] = 1.e-4
 params[:relTol] = 1.e-2
 

docs/src/examples/exampleCS.jl

@@ -1,4 +1,4 @@
-using PyPlot, MRIReco
+using PyPlot, MRIReco, MRIReco.RegularizedLeastSquares
 
 # load fully sampled data
 f = ISMRMRDFile(@__DIR__()*"/data/knee_3dFSE_slice170.h5")
@@ -32,11 +32,10 @@ params[:reco] = "multiCoil"
 params[:reconSize] = (320,320)
 params[:senseMaps] = smaps
 
-params[:solver] = "cgnr"
-params[:regularization] = "L2"
-params[:λ] = 1.e-4
+params[:solver] = CGNR
+params[:reg] = L2Regularization(1.e-4)
 params[:iterations] = 5
-params[:normalizeReg] = true
+params[:normalizeReg] = MeasurementBasedNormalization()
 
 img_cg = reconstruction(acqDataSub, params)
 
@@ -47,15 +46,14 @@ params[:reco] = "multiCoil"
 params[:reconSize] = (320,320)
 params[:senseMaps] = smaps
 
-params[:solver] = "admm"
-params[:regularization] = "TV"
-params[:λ] = 1.e-1 # 5.e-2
+params[:solver] = ADMM
+params[:reg] = TVRegularization(1.e-1, shape = (320, 320))
 params[:iterations] = 50
 params[:ρ] = 0.1
 params[:absTol] = 1.e-4
 params[:relTol] = 1.e-2
 params[:tolInner] = 1.e-2
-params[:normalizeReg] = true
+params[:normalizeReg] = MeasurementBasedNormalization()
 
 img_tv = reconstruction(acqDataSub, params)
 

docs/src/examples/exampleCustom.jl

@@ -1,4 +1,4 @@
-using Wavelets, DelimitedFiles, LinearAlgebra, PyPlot, MRIReco
+using Wavelets, DelimitedFiles, LinearAlgebra, PyPlot, MRIReco, MRIReco.RegularizedLeastSquares
 
 function analyzeImage(x::Vector{T},D::Matrix{T},xsize::NTuple{2,Int64},psize::NTuple{2,Int64};t0::Int64=size(D,2),tol=1e-3) where T
   nx,ny = xsize
@@ -66,11 +66,10 @@ params = Dict{Symbol,Any}()
 params[:reco] = "standard"
 params[:reconSize] = (nx,ny)
 params[:iterations] = 50
-params[:λ] = 2.e-2
-params[:regularization] = "L1"
+params[:reg] = L1Regularization(2.e-2)
 params[:sparseTrafo] = dictOp(D,(nx,ny),(px,py),2.e-2)
 params[:ρ] = 0.1
-params[:solver] = "admm"
+params[:solver] = ADMM
 params[:absTol] = 1.e-4
 params[:relTol] = 1.e-2
 

docs/src/examples/exampleFieldmap.jl

@@ -1,4 +1,4 @@
-using MRIReco
+using MRIReco, MRIReco.RegularizedLeastSquares
 
 ##### simple example ####
 
@@ -32,9 +32,9 @@ exportImage(filename, abs.(Ireco[:,:,1,1,1]) )
 
 # now with fieldmap correction
 params[:reco] = "standard"
-params[:regularization] = "L2"
+params[:reg] = L2Regularization(0.0)
 params[:iterations] = 3
-params[:solver] = "admm"
+params[:solver] = ADMM
 params[:correctionMap] = cmap
 params[:alpha] = 1.75
 params[:m] = 4.0

docs/src/examples/exampleParallel/reconstruction.jl

@@ -1,4 +1,4 @@
-using MRIReco, FFTW, LinearAlgebra, BenchmarkTools
+using MRIReco, FFTW, LinearAlgebra, BenchmarkTools, MRIReco.RegularizedLeastSquares
 
 FFTW.set_num_threads(1);BLAS.set_num_threads(1)
 
@@ -16,10 +16,9 @@ acqData = AcquisitionData(raw)
 params = Dict{Symbol, Any}()
 params[:reco] = "multiCoil"
 params[:reconSize] = (N,N)
-params[:regularization] = "L2"
-params[:λ] = 1.e-3
+params[:reg] = L2Regularization(1.e-3)
 params[:iterations] = 40
-params[:solver] = "cgnr"
+params[:solver] = CGNR
 params[:senseMaps] = coilsens
 #params[:correctionMap] = cmap
 

docs/src/examples/exampleSENSE.jl

@@ -1,4 +1,4 @@
-using PyPlot, MRIReco
+using PyPlot, MRIReco, MRIReco.RegularizedLeastSquares
 
 ##### simple example ####
 
@@ -26,10 +26,9 @@ acqData = simulation(I, params)
 params = Dict{Symbol, Any}()
 params[:reco] = "multiCoil"
 params[:reconSize] = (N,N)
-params[:regularization] = "L2"
-params[:λ] = 1.e-3
+params[:reg] = L2Regularization(1.e-3)
 params[:iterations] = 40
-params[:solver] = "cgnr"
+params[:solver] = CGNR
 params[:senseMaps] = coilsens
 params[:toeplitz] = false
 @time Ireco = reconstruction(acqData, params)

docs/src/overview.md

@@ -11,7 +11,7 @@ following graph, the most important (not all) dependencies of MRIReco are visual
 
 Most importantly, all iterative solvers are implemented in RegularizedLeastSquares.jl
 so that MRIReco can benefit from all improvements made in that package. Gridding
-is implemented in the NFFT.jl package, which has many applications byond MRI.
+is implemented in the NFFT.jl package, which has many applications beyond MRI.
 Sparsifying transformations are usually also not MRI specific and therefore implemented
 in independent packages (e.g. Wavelets.jl). For storing image data MRIReco.jl uses
 NiFTI.jl. Dicom data can potentially be saved by the DICOM.jl package, which, however,

examples/mridataorg/example.jl

@@ -10,7 +10,7 @@ end
 # Download data
 include("downloadData.jl")
 
-using PyPlot, MRIReco, MRIFiles, MRICoilSensitivities
+using PyPlot, MRIReco, MRIFiles, MRICoilSensitivities, MRIReco.RegularizedLeastSquares, FFTW
 
 ##################
 ## Data Loading ##
@@ -45,17 +45,16 @@ smaps = espirit(acqData2d, (6,6), 30, eigThresh_1=0.04, eigThresh_2=0.98)
 params = Dict{Symbol, Any}()
 params[:reco] = "multiCoil"
 params[:reconSize] = Tuple(acqData2d.encodingSize[1:2])
-params[:solver] = "admm"
-params[:regularization] = "L1"
+params[:solver] = ADMM
+params[:reg] = L1Regularization(2.e-1)
 params[:sparseTrafo] = "Wavelet"
-params[:λ] = 2.e-1
 params[:iterations] = 30
 params[:ρ] = 0.1
 params[:absTol] = 1.e-4
 params[:relTol] = 1.e-3
 params[:tolInner] = 1.e-2
 params[:senseMaps] = smaps
-params[:normalizeReg] = true
+params[:normalizeReg] = MeasurementBasedNormalization()
 
 ############################
 ## Perform reconstruction ##

src/MRIReco.jl

@@ -20,7 +20,6 @@ include("Reconstruction/Reconstruction.jl")
 function __init__()
   if Threads.nthreads() > 1
     BLAS.set_num_threads(1)
-    FFTW.set_num_threads(1)
   elseif Sys.iswindows()
     BLAS.set_num_threads(1) # see https://github.com/JuliaLang/julia/issues/36976
   end