From 827c446b691144a964bf6a04cf6d69c1ba867e7c Mon Sep 17 00:00:00 2001 From: aTrotier Date: Wed, 6 Mar 2024 10:54:57 +0100 Subject: [PATCH] update reco with only a notebook v0.52 --- .../RECO_JULIA_A_MP2RAGE_CS/README.md | 109 +- .../notebook_MP2RAGE.jl | 2460 +++++++++++++++++ .../{ => old_reco}/Manifest.toml | 0 .../{ => old_reco}/Project.toml | 0 .../old_reco/README.md | 29 + .../{ => old_reco}/main.jl | 2 +- .../{ => old_reco}/utils_a_MP2RAGE_CS.jl | 0 SEQ/README.md | 11 +- 8 files changed, 2577 insertions(+), 34 deletions(-) create mode 100644 RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/notebook_MP2RAGE.jl rename RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/{ => old_reco}/Manifest.toml (100%) rename RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/{ => old_reco}/Project.toml (100%) create mode 100644 RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/README.md rename RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/{ => old_reco}/main.jl (71%) rename RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/{ => old_reco}/utils_a_MP2RAGE_CS.jl (100%) diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/README.md b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/README.md index 3a7a422..448db9d 100644 --- a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/README.md +++ b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/README.md @@ -1,48 +1,99 @@ # Reconstruction of MP2RAGE acquisition with Julia +Reconstruction was performed Online and Offline. The Online version is not maintained anymore (I do not have access to a scanner with Centos 7 but if needed I can help you with that. + +Only an offline reconstruction that send back a nifti file is working using a Pluto notebook. # Information about Julia -## Install Julia -- Download and install Julia : https://julialang.org/downloads/ +## Julia Installation -The generic Linux and FreeBSD binaries do not require any special installation steps, but you will need to ensure that your system can find the julia executable. The directory where Julia is installed is referred to as . +To use the code, we recommend downloading Julia version 1.9.3 with `juliaup`. -To run Julia, you can do any of the following: -- Invoke the julia executable by using its full path: /bin/julia -- Create a symbolic link to julia inside a folder which is on your system PATH -- Add Julia's bin folder (with full path) to your system PATH environment variable +
+Windows -To add Julia's bin folder (with full path) to PATH environment variable, you can edit the ~/.bashrc (or ~/.bash_profile) file. Open the file in your favourite editor and add a new line as follows: +#### 1. Install juliaup +``` +winget install julia -s msstore +``` +#### 2. Add Julia 1.9.3 +``` +juliaup add 1.9.3 +``` +#### 3. Make 1.9.3 default +``` +juliaup default 1.9.3 +``` -```bash -export PATH="$PATH:/path/to//bin" + + +
+ + +
+Mac + +#### 1. Install juliaup +``` +curl -fsSL https://install.julialang.org | sh ``` +You may need to run `source ~/.bashrc` or `source ~/.bash_profile` or `source ~/.zshrc` if `juliaup` is not found after installation. -## Launch Julia -Type `julia` in your terminal. The most important options you can add are : -- `-t auto` or `-t N` où N est le nombre de threads que vous voulez utiliser -- `--project PATH` let julia read the project and manifest in the directory **PATH** +Alternatively, if `brew` is available on the system you can install juliaup with +``` +brew install juliaup +``` +#### 2. Add Julia 1.9.3 +``` +juliaup add 1.9.3 +``` +#### 3. Make 1.9.3 default +``` +juliaup default 1.9.3 +``` + + -# Reconstruction -The reconstruction can be performed either directly on the Bruker scanner by calling a macro. The results will be available in a 2dseq files and can be seen directly in Paravision. -Or you can reconstruct offline the data and write directly the nifti (without any information about the FOV position etc) +
-Two packages are required : -- `MRIReco` : read bruker files and perform advanced reconstruction -- `qMRI` : process the image and create T1 maps +
+Linux -Some functions are also requires and stores in 2 files : -- `utils_a_MP2RAGE_CS.jl` : Reorder the fid data according to the Compressed Sensing sampling patterns. Additionnal functions to extract the kspace and crop the center. -- `utils_write_bruker.jl` : write the resulting image in the 2dseq files and edit the `VISU_PARS` +#### 1. Install juliaup -## Offline reconstruction -In order to perform an offline reconstruction (without writing to the 2dseq folder) use the `main.jl` script. -Just edit the path to your experiment : -```julia -b = BrukerFile(PATH) ``` +curl -fsSL https://install.julialang.org | sh +``` +You may need to run `source ~/.bashrc` or `source ~/.bash_profile` or `source ~/.zshrc` if `juliaup` is not found after installation. + +Alternatively, use the AUR if you are on Arch Linux or `zypper` if you are on openSUSE Tumbleweed. +#### 2. Add Julia 1.9.3 +``` +juliaup add 1.9.3 +``` +#### 3. Make 1.9.3 default +``` +juliaup default 1.9.3 +``` +
-If you want to write the file to nifti you can run the 3 last lines. +# Offline reconstruction : output nifti files +The reconstruction can be performed with a pluto notebook. +## We first need to install Pluto. +- launch julia : `julia -t auto` +- type `]`, the prompt should turn blue (rather than green) +- type `add Pluto` +- close the terminal +## Run the notebook +- open a terminal +- `julia -t auto` +- `using Pluto` +- `Pluto.run()` should open a page in your web browser +- Open the `notebook_MP2RAGE.jl` files (it should open in safemode) +- Edit the specific paths (bruker, nifti output) +- run it :) \ No newline at end of file diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/notebook_MP2RAGE.jl b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/notebook_MP2RAGE.jl new file mode 100644 index 0000000..bb99564 --- /dev/null +++ b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/notebook_MP2RAGE.jl @@ -0,0 +1,2460 @@ +### A Pluto.jl notebook ### +# v0.19.40 + +using Markdown +using InteractiveUtils + +# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error). +macro bind(def, element) + quote + local iv = try Base.loaded_modules[Base.PkgId(Base.UUID("6e696c72-6542-2067-7265-42206c756150"), "AbstractPlutoDingetjes")].Bonds.initial_value catch; b -> missing; end + local el = $(esc(element)) + global $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : iv(el) + el + end +end + +# ╔═╡ 0c35cd94-b120-11ed-39b9-63f98b2d4b66 +begin + using CairoMakie, PlutoUI, MRIReco, MRICoilSensitivities, MRIFiles, QuantitativeMRI, Statistics, NIfTI +end + +# ╔═╡ 51725380-d445-47ae-9a54-05d5e3611b58 +md"# Introduction + +This notebook will reconstruct the TI_1, TI_2, MP2RAGE and T1 maps of this sequence : +https://github.com/aTrotier/SEQ\_BRUKER\_A\_MP2RAGE\_CS\_PUBLIC + +It has been tested for : +- v0.52 +- Fully sampled acquisition where Ny = ETL (you should see an image on the Bruker scanner) + +In order to work, an additionnal files is required + +--- +## Packages +Multiple packages are required, the package versions are stored into this notebook : +- CairoMakie : for plot +- MRIReco : reconstruction +- MRIFiles : reading Bruker rawdatasets +- QuantitativeMRI : create T1 maps from MP2RAGE acquisition +- NIfTI : output images format" + +# ╔═╡ 1e68c7eb-7fc0-4867-bd10-21077e7bf7b6 +md"## Parameters to update before reconstruction +You should edit the following cells : +- `fid_path` should point to the bruker folder experiment +- `ni_folder` should point to the folder where the nifti should be stored +- `ni_basename` is the name of the nifti files" + +# ╔═╡ a004ad9d-5ab1-47ec-a5b2-d0b6425d1da5 +begin + fid_path = "/Users/aurelien/Documents/GitHub/SEQ_BRUKER_A_MP2RAGE_CS_PUBLIC/DATA/8" + + ni_folder="/Users/aurelien/Documents/GitHub/SEQ_BRUKER_A_MP2RAGE_CS_PUBLIC/DATA" + ni_basename = "ni_" + + sl = 50 # default slice to show +end + +# ╔═╡ a7588a2a-f4b5-4e46-8263-f492c7e73af0 +""" +RawAcquisitionData_MP2RAGE_CS(b::BrukerFile) + + Specific function that reorder the lines to create a RawAcquisition Object in the right format +""" +function RawAcquisitionData_MP2RAGE_CS(b::BrukerFile) + # extract parameters + sx = MRIFiles.acqSize(b)[1] + sy = MRIFiles.pvmMatrix(b)[2] + sz = MRIFiles.pvmMatrix(b)[3] + RareFact = parse.(Int,b["RareFactor"]) + + # extract position of rawdata + GradPhaseVect = parse.(Float32,b["GradPhaseVector"]) + GradPhaseVect=GradPhaseVect*sy/2; + GradPhaseVect=round.(Int,(GradPhaseVect.-minimum(GradPhaseVect))); + + GradSliceVect = parse.(Float32,b["GradSliceVector"]) + GradSliceVect=GradSliceVect*sz/2; + GradSliceVect=round.(Int,(GradSliceVect.-minimum(GradSliceVect))) + + #= + mask = zeros(Int,(sy,sz)) + anim = @animate for i = 1 : 100#length(GradPhaseVect) + mask[GradPhaseVect[i],GradSliceVect[i]]=1; + heatmap(mask,color = :greys,aspect_ratio = 1,legend = :none , axis=nothing,lims=(1,sz)) + end + gif(anim, "anim_fps15.gif", fps = 15) + =# + + # read data + dtype = Complex{MRIFiles.acqDataType(b)} + filename = joinpath(b.path, "fid") + + N = MRIFiles.acqSize(b) + numChannel = parse.(Int,b["PVM_EncNReceivers"]) + profileLength = Int((ceil(N[1]*numChannel*sizeof(dtype)/1024))*1024/sizeof(dtype)) # number of points + zeros + + RareFact = MRIFiles.acqRareFactor(b) + numSlices = MRIFiles.acqNumSlices(b) + numEchos = MRIFiles.acqNumEchos(b) + numEncSteps2 = length(N) == 3 ? N[3] : 1 + numRep = MRIFiles.acqNumRepetitions(b) + + I = open(filename,"r") do fd + read!(fd,Array{dtype,5}(undef, profileLength, + RareFact, + numEchos, + div(N[2], RareFact), + numRep))[1:N[1]*numChannel,:,:,:,:] + end; + + I2 = permutedims(I,(1,2,4,3,5)); # put echos in last dimension + I2 = reshape(I2,sx,numChannel,N[2],numEchos,numRep) + + + objOrd = MRIFiles.acqObjOrder(b) + objOrd = objOrd.-minimum(objOrd) + + gradMatrix = MRIFiles.acqGradMatrix(b) + + offset1 = MRIFiles.acqReadOffset(b) + offset2 = MRIFiles.acqPhase1Offset(b) + offset3 = ndims(b) == 2 ? MRIFiles.acqSliceOffset(b) : MRIFiles.pvmEffPhase2Offset(b) + + profiles = MRIBase.Profile[] + for nR = 1:numRep + for nEcho=1:numEchos + for nEnc = 1:N[2] + + counter = EncodingCounters(kspace_encode_step_1=GradPhaseVect[nEnc], + kspace_encode_step_2=GradSliceVect[nEnc], + average=0, + slice=0, + contrast=nEcho-1, + phase=0, + repetition=nR-1, + set=0, + segment=0) + + nSl = 1 + G = gradMatrix[:,:,nSl] + read_dir = (G[1,1],G[2,1],G[3,1]) + phase_dir = (G[1,2],G[2,2],G[3,2]) + slice_dir = (G[1,3],G[2,3],G[3,3]) + + # Not sure if the following is correct... + pos = offset1[nSl]*G[:,1] + + offset2[nSl]*G[:,2] + + offset3[nSl]*G[:,3] + + position = (pos[1], pos[2], pos[3]) + + head = AcquisitionHeader(number_of_samples=sx, idx=counter, + read_dir=read_dir, phase_dir=phase_dir, + slice_dir=slice_dir, position=position, + center_sample=div(sx,2), + available_channels = numChannel, #TODO + active_channels = numChannel) + traj = Matrix{Float32}(undef,0,0) + dat = map(ComplexF32, reshape(I2[:,:,nEnc,nEcho,nR],:,numChannel)) + push!(profiles, MRIBase.Profile(head,traj,dat) ) + end + end + end + params = Dict{String,Any}() + params["trajectory"] = "Cartesian" + params["encodedSize"] = [sx;sy;sz] + F = MRIFiles.acqFov(b) + params["encodedFOV"] = F*1000.0 #convert m to mm + params["receiverChannels"] = numChannel + params["H1resonanceFrequency_Hz"] = round(Int, parse(Float64,b["SW"])*1000000) + params["studyID"] = b["VisuStudyId"] + #params["studyDescription"] = b["ACQ_scan_name"] + #params["studyInstanceUID"] = + params["referringPhysicianName"] = MRIFiles.latin1toutf8(b["ACQ_operator"]) + + params["patientName"] = b["VisuSubjectName"] + + params["measurementID"] = parse(Int64,b["VisuExperimentNumber"]) + params["seriesDescription"] = b["ACQ_scan_name"] + + params["institutionName"] = MRIFiles.latin1toutf8(b["ACQ_institution"]) + params["stationName"] = b["ACQ_station"] + params["systemVendor"] = "Bruker" + + params["TR"] = parse.(Float32,b["RecoveryTime"]) + params["delta_TR"] = MRIFiles.acqRepetitionTime(b) + params["TE"] = parse.(Float32,b["PVM_EchoTime"]) + params["TI"] = parse.(Float32,b["EffectiveTE"]) + params["flipAngle_deg"] = parse.(Int64,[split(b["ExcPulse1"], ", ")[3];split(b["ExcPulse2"], ", ")[3]]) + params["sequence_type"] = MRIFiles.acqProtocolName(b) + params["echo_spacing"] = MRIFiles.acqInterEchoTime(b) + + raw = RawAcquisitionData(params, profiles); + return raw +end + +# ╔═╡ 7fc4c6ec-a1f8-4984-b5bd-edf913bd56d3 +md"# Load and show 2dseq + +if the images is reconstructed directly on the scanner (Ny = ETL) we can see the images + +But because it is a magnitude images we can't performed the MP2RAGE combinaison and then compute the T1 map" + +# ╔═╡ 78747860-58b4-4fab-993c-1f38f74b3754 +begin + b=BrukerFile(fid_path) + im_sos = recoData(b,1) + SpatialResolution = Tuple(parse.(Float32,b["PVM_SpatResol"])) +end; + +# ╔═╡ 826d5bb7-d5b8-4c84-8798-d1829105a9cf +md"slider that control the slice" + +# ╔═╡ fcaf746f-108b-44b9-a7f8-cdf89f5d2fe9 +@bind sl_1 PlutoUI.Slider(1:1:size(im_sos,3), default=ceil(Int,size(im_sos,3)/2)) + +# ╔═╡ f929c1b6-1c1c-48b3-a607-24e874702285 +let + f = Figure() + heatmap(f[1,1],im_sos[:,:,sl_1,1]) + heatmap(f[1,2],im_sos[:,:,sl_1,2]) + f +end + +# ╔═╡ 282b6e60-78c6-4d49-b16d-2688d285c94e +md"# MP2RAGE reconstruction from FID rawdata + +### 1) Perform the reconstruction from FID in order to get complex image" + +# ╔═╡ a434e90f-b323-4ce5-84fc-38742b298ec4 +begin + raw = RawAcquisitionData_MP2RAGE_CS(b); + acq = AcquisitionData(raw,OffsetBruker = true); + + @info "FFT reconstruction" + params = Dict{Symbol, Any}() + params[:reco] = "direct" + params[:reconSize] = tuple(acq.encodingSize...) + Ireco = reconstruction(acq, params); + + sens = estimateCoilSensitivities(Ireco[:,:,:,2:2,:,1:1], 1.e-2) + Icomb = sum(conj.(sens).*Ireco,dims=5) ./sum(abs.(sens).^2,dims = 5) +end; + +# ╔═╡ 87aa1b59-c9f1-492b-9a6b-04d7e698c03a +heatmap(abs.(Icomb[:,:,sl_1,2,1,1])) + +# ╔═╡ f3043546-969d-409f-93b1-4e882764c41a +md"### 2) Average the NR" + +# ╔═╡ ef5e16e6-7fcb-4257-ab10-45479fe84b86 +Imean = mean(Icomb[:,:,:,:,:,:],dims = 6)[:,:,:,:,1,1]; + +# ╔═╡ 3a5c1260-b398-4d3a-b3a7-2f028b1295f2 +begin + # apply MP2RAGE + MP2 = mp2rage_comb(Imean) + + TI₁ = parse(Float64,b["EffectiveTE"][1]) + TI₂ = parse(Float64,b["EffectiveTE"][2]) + TR = parse(Float64,b["PVM_RepetitionTime"]) + MP2RAGE_TR = parse(Float64,b["RecoveryTime"]) + ETL = parse(Int64,b["RareFactor"]) + α₁ = parse.(Float64,split(b["ExcPulse1"],", ")[3]) + α₂ = parse.(Float64,split(b["ExcPulse2"],", ")[3]) + + params_MP2 = ParamsMP2RAGE(TI₁,TI₂,TR,MP2RAGE_TR,ETL,α₁,α₂) + T1map, = mp2rage_T1maps(MP2,params_MP2) +end; + +# ╔═╡ 110345ef-c438-4abd-8b09-1fb057f43839 +@bind sl_2 PlutoUI.Slider(1:1:size(T1map,3), default=ceil(Int,size(T1map,3)/2)) + +# ╔═╡ 91bb3f1e-a1d5-437f-8a02-57e81d4951de + let + f=Figure() + ax=Axis(f[1,1],title = "MP2RAGE",aspect=SpatialResolution[2]/SpatialResolution[1]) + heatmap!(ax,abs.(MP2[:,:,sl_2])) + hidedecorations!(ax) + ax=Axis(f[1,2],title = "MP2RAGE",aspect=SpatialResolution[2]/SpatialResolution[1]) + h=heatmap!(ax,abs.(T1map[:,:,sl_2]),aspect = 1) + hidedecorations!(ax) + Colorbar(f[1,end+1],h,label = "T1 [ms]") + f + end + +# ╔═╡ 7c17ca8c-76b6-4188-b654-f74ebf3d8897 +md"# Export Data to nifti" + +# ╔═╡ a12f0b7d-7c9f-4745-85ab-f58a7432a66c +begin + ni = NIVolume(T1map,voxel_size = SpatialResolution) + niwrite(ni_folder*"/T1_"*ni_basename*".nii",ni) + + ni = NIVolume(MP2,voxel_size = SpatialResolution) + niwrite(ni_folder*"/MP2_"*ni_basename*".nii",ni) + + ni = NIVolume(abs.(Imean),voxel_size = SpatialResolution) + niwrite(ni_folder*"/TI_"*ni_basename*".nii",ni) +end + +# ╔═╡ 00000000-0000-0000-0000-000000000001 +PLUTO_PROJECT_TOML_CONTENTS = """ +[deps] +CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" +MRICoilSensitivities = "c57eb701-aafc-44a2-a53c-128049758959" +MRIFiles = "5a6f062f-bf45-497d-b654-ad17aae2a530" +MRIReco = 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+version = "5.8.0+1" + +[[deps.libevent_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "OpenSSL_jll"] +git-tree-sha1 = "f04ec6d9a186115fb38f858f05c0c4e1b7fc9dcb" +uuid = "1080aeaf-3a6a-583e-a51c-c537b09f60ec" +version = "2.1.13+1" + +[[deps.libfdk_aac_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "daacc84a041563f965be61859a36e17c4e4fcd55" +uuid = "f638f0a6-7fb0-5443-88ba-1cc74229b280" +version = "2.0.2+0" + +[[deps.libpng_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Zlib_jll"] +git-tree-sha1 = "1ea2ebe8ffa31f9c324e8c1d6e86b4165b84a024" +uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f" +version = "1.6.43+0" + +[[deps.libsixel_jll]] +deps = ["Artifacts", "JLLWrappers", "JpegTurbo_jll", "Libdl", "Pkg", "libpng_jll"] +git-tree-sha1 = "d4f63314c8aa1e48cd22aa0c17ed76cd1ae48c3c" +uuid = "075b6546-f08a-558a-be8f-8157d0f608a5" +version = "1.10.3+0" + +[[deps.libvorbis_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Ogg_jll", "Pkg"] +git-tree-sha1 = "b910cb81ef3fe6e78bf6acee440bda86fd6ae00c" +uuid = "f27f6e37-5d2b-51aa-960f-b287f2bc3b7a" +version = "1.3.7+1" + +[[deps.nghttp2_jll]] +deps = ["Artifacts", "Libdl"] +uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d" +version = "1.52.0+1" + +[[deps.p7zip_jll]] +deps = ["Artifacts", "Libdl"] +uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0" +version = "17.4.0+2" + +[[deps.prrte_jll]] +deps = ["Artifacts", "Hwloc_jll", "JLLWrappers", "Libdl", "PMIx_jll", "libevent_jll"] +git-tree-sha1 = "5adb2d7a18a30280feb66cad6f1a1dfdca2dc7b0" +uuid = "eb928a42-fffd-568d-ab9c-3f5d54fc65b9" +version = "3.0.2+0" + +[[deps.x264_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "4fea590b89e6ec504593146bf8b988b2c00922b2" +uuid = "1270edf5-f2f9-52d2-97e9-ab00b5d0237a" +version = "2021.5.5+0" + +[[deps.x265_jll]] +deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"] +git-tree-sha1 = "ee567a171cce03570d77ad3a43e90218e38937a9" +uuid = "dfaa095f-4041-5dcd-9319-2fabd8486b76" +version = "3.5.0+0" +""" + +# ╔═╡ Cell order: +# ╟─51725380-d445-47ae-9a54-05d5e3611b58 +# ╠═0c35cd94-b120-11ed-39b9-63f98b2d4b66 +# ╟─1e68c7eb-7fc0-4867-bd10-21077e7bf7b6 +# ╠═a004ad9d-5ab1-47ec-a5b2-d0b6425d1da5 +# ╟─a7588a2a-f4b5-4e46-8263-f492c7e73af0 +# ╟─7fc4c6ec-a1f8-4984-b5bd-edf913bd56d3 +# ╠═78747860-58b4-4fab-993c-1f38f74b3754 +# ╟─f929c1b6-1c1c-48b3-a607-24e874702285 +# ╟─826d5bb7-d5b8-4c84-8798-d1829105a9cf +# ╟─fcaf746f-108b-44b9-a7f8-cdf89f5d2fe9 +# ╟─282b6e60-78c6-4d49-b16d-2688d285c94e +# ╠═a434e90f-b323-4ce5-84fc-38742b298ec4 +# ╟─87aa1b59-c9f1-492b-9a6b-04d7e698c03a +# ╟─f3043546-969d-409f-93b1-4e882764c41a +# ╠═ef5e16e6-7fcb-4257-ab10-45479fe84b86 +# ╠═3a5c1260-b398-4d3a-b3a7-2f028b1295f2 +# ╠═91bb3f1e-a1d5-437f-8a02-57e81d4951de +# ╟─110345ef-c438-4abd-8b09-1fb057f43839 +# ╟─7c17ca8c-76b6-4188-b654-f74ebf3d8897 +# ╠═a12f0b7d-7c9f-4745-85ab-f58a7432a66c +# ╟─00000000-0000-0000-0000-000000000001 +# ╟─00000000-0000-0000-0000-000000000002 diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/Manifest.toml b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/Manifest.toml similarity index 100% rename from RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/Manifest.toml rename to RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/Manifest.toml diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/Project.toml b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/Project.toml similarity index 100% rename from RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/Project.toml rename to RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/Project.toml diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/README.md b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/README.md new file mode 100644 index 0000000..5d7bd0e --- /dev/null +++ b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/README.md @@ -0,0 +1,29 @@ + +## Online Reconstruction (NOT MAINTAINED anymore moved into old_reco folder) +The reconstruction can be performed either directly on the Bruker scanner by calling a macro. The results will be available in a 2dseq files and can be seen directly in Paravision. +Or you can reconstruct offline the data and write directly the nifti (without any information about the FOV position etc) + +Two packages are required : +- `MRIReco` : read bruker files and perform advanced reconstruction +- `qMRI` : process the image and create T1 maps + +Some functions are also requires and stores in 2 files : +- `utils_a_MP2RAGE_CS.jl` : Reorder the fid data according to the Compressed Sensing sampling patterns. Additionnal functions to extract the kspace and crop the center. +- `utils_write_bruker.jl` : write the resulting image in the 2dseq files and edit the `VISU_PARS` + +## Launch Julia +Type `julia` in your terminal. The most important options you can add are : +- `-t auto` or `-t N` où N est le nombre de threads que vous voulez utiliser +- `--project PATH` let julia read the project and manifest in the directory **PATH** + + + +## Offline reconstruction +In order to perform an offline reconstruction (without writing to the 2dseq folder) use the `main.jl` script. +Just edit the path to your experiment : +```julia +b = BrukerFile(PATH) +``` + +If you want to write the file to nifti you can run the 3 last lines. + diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/main.jl b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/main.jl similarity index 71% rename from RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/main.jl rename to RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/main.jl index 9330a87..35dc37b 100644 --- a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/main.jl +++ b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/main.jl @@ -5,7 +5,7 @@ using MRIReco using qMRI include("utils_a_MP2RAGE_CS.jl") -b = BrukerFile("data/20220930_144024_AT_MP2RAGE_JULIA_05_1_1/5") +b = BrukerFile("/Users/aurelien/Documents/GitHub/SEQ_BRUKER_A_MP2RAGE_CS_PUBLIC/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/data/8") Ireco,MP2,T1map,acq,sens = recoMP2RAGE_CS(b, λ=0.1,iteration=30,zeroFilled = false) diff --git a/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/utils_a_MP2RAGE_CS.jl b/RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/utils_a_MP2RAGE_CS.jl similarity index 100% rename from RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/utils_a_MP2RAGE_CS.jl rename to RECO_a_MP2RAGE_CS/RECO_JULIA_A_MP2RAGE_CS/old_reco/utils_a_MP2RAGE_CS.jl diff --git a/SEQ/README.md b/SEQ/README.md index 8d070b1..f41cb16 100644 --- a/SEQ/README.md +++ b/SEQ/README.md @@ -1,7 +1,10 @@ # Information about sequence -Version of the sequence is available here : -https://github.com/aTrotier/SEQ_BRUKER_a_MP2RAGE_CS/tree/v0.51 +Version of the sequence is available here as release. You will find the compiled version of the sequence and a standard protocol : +https://github.com/aTrotier/SEQ_BRUKER_A_MP2RAGE_CS_PUBLIC/releases -# Latest modifications -- add ReleaseVersion in the sequence \ No newline at end of file +# release description +- v0.52 + - enable average : NA +- v0.51 + - add ReleaseVersion in the sequence \ No newline at end of file