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Merge pull request #389 from JuliaHealth/docs-citeus
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Adding "How to Cite Koma" section to docs
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@cncastillo
cncastillo authored May 5, 2024
2 parents f0d40c0 + 79e4539 commit 73d3c5d
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22 changes: 22 additions & 0 deletions docs/src/index.md
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```
We organized the documentation following the philosophy presented by [David Laing](https://documentation.divio.com/).

!!! details "How to Cite Koma"
If you use Koma, please cite our paper:

**Plain Text:**

Castillo-Passi, C, Coronado, R, Varela-Mattatall, G, Alberola-López, C, Botnar, R, Irarrazaval, P. KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration. Magn Reson Med. 2023; 1- 14. doi: 10.1002/mrm.29635

**BibTex:**

```bibtex
@article{https://doi.org/10.1002/mrm.29635,
author = {Castillo-Passi, Carlos and Coronado, Ronal and Varela-Mattatall, Gabriel and Alberola-López, Carlos and Botnar, René and Irarrazaval, Pablo},
title = {KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration},
journal = {Magnetic Resonance in Medicine},
keywords = {Bloch equations, GPU, GUI, Julia, open source, simulation},
doi = {https://doi.org/10.1002/mrm.29635},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.29635},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29635},
}
```

## Features

Some of the features of **KomaMRI** are:
* Fast simulations by using CPU and GPU parallelization 🏃💨.
* Open Source, so anyone can include additional features 🆙.
* Compatibility with community-standards 🤝 like Pulseq `.seq` and ISMRMRD `.mrd`.
* Compatibility with [Pluto](how-to/2-2-use-koma-notebooks.md#Pluto) and [Jupyter](how-to/2-2-use-koma-notebooks.md#Jupyter) notebooks 🎈
* Interactive visualizations using PlotlyJS.jl 📲
* Cross-platform 🌐 thanks to the use of the Julia programming language.
* Friendly user interface for people with no programming skills 😌.
* Flexible API for advanced users 👨‍💻.
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100 changes: 50 additions & 50 deletions examples/4.reproducible_notebooks/pluto-02-low-field-cmra-optimization.jl
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#> tags = ["CMRA", "Low Field", "Optimization"]
#> date = "2024-04-16"
#> description = "Optimizing sequence to improve SNR and fat supression."
#>
#>
#> [[frontmatter.author]]
#> name = "Carlos Castillo Passi"
#> url = "https://avatars.githubusercontent.com/u/5957134?s=400&u=fe62a2a899ced18e8b882cebde6b1eefe6a1222c&v=4"
Expand Down Expand Up @@ -90,7 +90,7 @@ begin
Trf = 500e-6 # 500 [ms]
B1 = 1 / (360*γ*Trf) # B1 amplitude [uT]
Tadc = 1e-6 # 1us

# Prepulses
Tfatsat = 26.624e-3 # 26.6 [ms]
T2prep_duration = 50e-3 # 50 [ms]
Expand All @@ -100,22 +100,22 @@ begin
dummy_heart_beats = 3 # Steady-state
TR = 5.3e-3 # 5.3 [ms] RF Low SAR
TE = TR / 2 # bSSFP condition
iNAV_lines = 6 # FatSat-Acq delay: iNAV_lines * TR
iNAV_lines = 6 # FatSat-Acq delay: iNAV_lines * TR
iNAV_flip_angle = 3.2 # 3.2 [deg]
im_segments = 20 # Acquisitino window: im_segments * TR

# To be optimized
im_flip_angle = 110 # 110 [deg]
FatSat_flip_angle = 180 # 180 [deg]

seq_params = (;
dummy_heart_beats,
seq_params = (;
dummy_heart_beats,
iNAV_lines,
im_segments,
iNAV_flip_angle,
im_segments,
iNAV_flip_angle,
im_flip_angle,
T2prep_duration,
FatSat_flip_angle,
T2prep_duration,
FatSat_flip_angle,
RR
)

Expand All @@ -125,7 +125,7 @@ end
# ╔═╡ a15d6b64-f8ee-4ee4-812c-d49cf5ea784d
md"""
## 1.4. Phantom
Each tissue was represented with 200 isochromats distributed along the $z$-axis to simulate gradient spoiling effects. The isochromats for each tissue were inside a 1D voxel of size $1.5\,\mathrm{mm}$. The values for $T_1$ and $T_2$ for blood, myocardial muscle, and fat at 0.55T were obtained from the work of Campbell-Washburn, et al. Fat spins were simulated using a chemical shift of $-3.4\,\mathrm{ppm}$, simulating regular fat with $T_1=183\,\mathrm{ms}$, and fast-recovering fat with $T_1=130\,\mathrm{ms}$.
Each tissue was represented with 200 isochromats distributed along the $z$-axis to simulate gradient spoiling effects. The isochromats for each tissue were inside a 1D voxel of size $1.5\,\mathrm{mm}$. The values for $T_1$ and $T_2$ for blood, myocardial muscle, and fat at 0.55T were obtained from the work of Campbell-Washburn, et al. Fat spins were simulated using a chemical shift of $-3.4\,\mathrm{ppm}$, simulating regular fat with $T_1=183\,\mathrm{ms}$, and fast-recovering fat with $T_1=130\,\mathrm{ms}$.
"""

# ╔═╡ f0a81c9f-5616-4663-948f-a4084e1719af
Expand Down Expand Up @@ -162,7 +162,7 @@ begin
end
return seq
end

function T2prep(TE; sample=false)
seq = Sequence()
seq += RF(90 * B1, Trf)
Expand All @@ -176,7 +176,7 @@ begin
end
return seq
end

function bSSFP(iNAV_lines, im_segments, iNAV_flip_angle, im_flip_angle; sample=false)
k = 0
seq = Sequence()
Expand Down Expand Up @@ -206,14 +206,14 @@ end
# ╔═╡ 7890f81e-cb15-48d2-a80c-9d73f9516056
begin
function CMRA(
dummy_heart_beats,
iNAV_lines,
im_segments,
iNAV_flip_angle,
dummy_heart_beats,
iNAV_lines,
im_segments,
iNAV_flip_angle,
im_flip_angle,
T2prep_duration=50e-3,
FatSat_flip_angle=180,
RR=1.0;
T2prep_duration=50e-3,
FatSat_flip_angle=180,
RR=1.0;
sample_recovery=zeros(Bool, dummy_heart_beats+1)
)
# Seq init
Expand All @@ -228,15 +228,15 @@ begin
seq += t2p
seq += fatsat
seq += bssfp
# RR interval consideration
# RR interval consideration
RRdelay = RR - dur(bssfp) - dur(t2p) - dur(fatsat)
seq += sample ? ADC(80, RRdelay) : Delay(RRdelay)
end
return seq
end

md"""- `CMRA` (show/hide code)
```julia
# Seq init
seq = Sequence()
Expand All @@ -249,7 +249,7 @@ begin
seq += t2p
seq += fatsat
seq += bssfp
# RR interval consideration
# RR interval consideration
RRdelay = RR - dur(bssfp) - dur(t2p) - dur(fatsat)
seq += Delay(RRdelay)
end
Expand All @@ -259,9 +259,9 @@ end
# ╔═╡ f57a2b6c-eb4c-45bd-8058-4a60b038925d
begin
function cardiac_phantom(off; off_fat=fat_freq)
myocard = Phantom{Float64}(x=dx, ρ=0.6*ones(Niso), T1=701e-3*ones(Niso),
myocard = Phantom{Float64}(x=dx, ρ=0.6*ones(Niso), T1=701e-3*ones(Niso),
T2=58e-3*ones(Niso), Δw=2π*off*ones(Niso))
blood = Phantom{Float64}(x=dx, ρ=0.7*ones(Niso), T1=1122e-3*ones(Niso),
blood = Phantom{Float64}(x=dx, ρ=0.7*ones(Niso), T1=1122e-3*ones(Niso),
T2=263e-3*ones(Niso), Δw=2π*off*ones(Niso))
fat1 = Phantom{Float64}(x=dx, ρ=1.0*ones(Niso), T1=183e-3*ones(Niso),
T2=93e-3*ones(Niso), Δw=2π*(off_fat + off)*ones(Niso))
Expand All @@ -276,7 +276,7 @@ end
# ╔═╡ f21e9e59-25c3-4f06-8de4-792cb305eb01
md"""# 2. Simulation
Two simulation experiments were performed to optimize the sequence parameters, (1) to optimize the imaging flip angle, and (2) to optimize the FatSat flip angle.
Two simulation experiments were performed to optimize the sequence parameters, (1) to optimize the imaging flip angle, and (2) to optimize the FatSat flip angle.
"""

Expand Down Expand Up @@ -312,16 +312,16 @@ plot_seq(seq; show_adc=true, range=[2900, 3325], slider=true)
begin
phantom_T1 = plot(
scatter(
x=obj.x * 1e3,
y=obj.T1 * 1e3,
x=obj.x * 1e3,
y=obj.T1 * 1e3,
mode="markers",
marker=attr(;
color=obj.T1 * 1e3,
color=obj.T1 * 1e3,
colorscale=[
[0.0, "black"],
[183.0/maximum(obj.T1 .* 1e3), "green"],
[701.0/maximum(obj.T1 .* 1e3), "blue"],
[1122.0/maximum(obj.T1 .* 1e3), "red"],
[701.0/maximum(obj.T1 .* 1e3), "blue"],
[1122.0/maximum(obj.T1 .* 1e3), "red"],
],
cmin=0.0,
cmax=1122.0,
Expand All @@ -345,16 +345,16 @@ begin
)
phantom_T2 = plot(
scatter(
x=obj.x * 1e3,
y=obj.T2 * 1e3,
x=obj.x * 1e3,
y=obj.T2 * 1e3,
mode="markers",
marker=attr(;
color=obj.T2 * 1e3,
color=obj.T2 * 1e3,
colorscale=[
[0.0, "black"],
[58.0/maximum(obj.T2 .* 1e3), "blue"],
[93.0/maximum(obj.T2 .* 1e3), "green"],
[263.0/maximum(obj.T2 .* 1e3), "red"],
[263.0/maximum(obj.T2 .* 1e3), "red"],
],
cmin=0.0,
cmax=263.0,
Expand Down Expand Up @@ -391,31 +391,31 @@ begin

# Plot
p0 = make_subplots(
rows=2,
cols=1,
subplot_titles=["Mxy" "Mz" "Sequence"],
shared_xaxes=true,
rows=2,
cols=1,
subplot_titles=["Mxy" "Mz" "Sequence"],
shared_xaxes=true,
vertical_spacing=0.1
)
for i=eachindex(spin_group)
p1 = scatter(
x=t, y=Mxy(i),
name=labs[i],
legendgroup=labs[i],
x=t, y=Mxy(i),
name=labs[i],
legendgroup=labs[i],
marker_color=cols[i]
)
p2 = scatter(
x=t,
y=Mz(i),
name=labs[i],
legendgroup=labs[i],
showlegend=false,
x=t,
y=Mz(i),
name=labs[i],
legendgroup=labs[i],
showlegend=false,
marker_color=cols[i]
)
add_trace!(p0, p1, row=1, col=1)
add_trace!(p0, p2, row=2, col=1)
end
relayout!(p0,
relayout!(p0,
yaxis_range=[0, 0.4],
xaxis_range=[RR*dummy_heart_beats, RR*dummy_heart_beats+.250]
)
Expand Down Expand Up @@ -548,7 +548,7 @@ begin
name="|Blood-Myoc|",legendgroup="|Blood-Myoc|",
showlegend=false,
fill="toself",
fillcolor="rgba(255,0,255,0.2)",
fillcolor="rgba(255,0,255,0.2)",
line=attr(color="rgba(0,0,0,0)"),
hoverinfo="none"
)
Expand Down Expand Up @@ -702,7 +702,7 @@ md"""# References
# ╔═╡ abea2c43-d83e-4438-8cd3-4be06b8174b3
md"""# Reproducibility
This [Pluto notebook](https://plutojl.org/) it is reproducible by defaults, as it has an embedded `Project.toml` and `Manifest.toml`, that store the exact package versions used to create this notebook."""
This [Pluto notebook](https://plutojl.org/) is reproducible by default, as it has an embedded `Project.toml` and `Manifest.toml`, that store the exact package versions used to create the notebook."""

# ╔═╡ 00000000-0000-0000-0000-000000000001
PLUTO_PROJECT_TOML_CONTENTS = """
Expand Down

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