High level functions for plotting 3D volumes

These are helper functions for plotting Volume3D objects using Makie. To make them available one must first load Makie or equivalent (i.e CairoMakie)

Show MNI-ICBM152 template contours with tissue masks overlays

using CairoMakie
using Minc2

# read T1w scan
icbm=Minc2.read_volume("mni_icbm152_t1_tal_nlin_sym_09c.mnc", store=Float64)
# read label mask, represent it as array of bytes 
lab=Minc2.read_volume("mni_icbm152_cls_tal_nlin_sym_09c.mnc", store=UInt8)


fig = Figure()
gc = fig[1, 1] = GridLayout()

Minc2.draw_outline_with_labels(gc, icbm, lab, 
    labels=Dict([1=>"CSF",2=>"GM",3=>"WM"]),
    nslices = 5)

resize_to_layout!(fig)

save("mni_icbm152_segmentation.png", fig, px_per_unit = 1)

Will produce

draw_outline_with_labels(
    layout, 
    anat, 
    seg; 
    labels, 
    cmap = :rainbow,
    levels = [20,30],
    show_colorbar = true,
    nslices = 4)

Show MNI-ICBM152 template contours with GM proability map

using CairoMakie
using Minc2

# read T1w scan
anat=Minc2.read_volume("mni_icbm152_t1_tal_nlin_sym_09c.mnc",store=Float64)
# read field
gm=Minc2.read_volume("mni_icbm152_gm_tal_nlin_sym_09c.mnc",store=Float64)

fig = Figure()
gc = fig[1, 1] = GridLayout()

# set background to transparent
Minc2.array(gm)[Minc2.array(gm) .< 1e-6] .= NaN

Minc2.draw_outline_with_heatmap(gc, anat, gm, 
    heat_limits=(0.0,1.0),cmap=:turbo,
    nslices = 5)

resize_to_layout!(fig)

save("mni_icbm152_gm.png", fig, px_per_unit = 1) 

Will produce

draw_outline_with_heatmap(
    layout, anat, heat; 
    cmap=:rainbow, levels=[20, 40],
    heat_limits=nothing, 
    show_colorbar=true,
    nslices=4)

Show two-tailed t-statistics on DBM style analysis

using CairoMakie
using Minc2

# read T1w scan and crop black area around ROI
anat=Minc2.crop_volume(
    Minc2.read_volume("mni_icbm152_t1_tal_nlin_sym_09c.mnc",store=Float64),
    [[15,15],[20,20],[20,20]])

# Read brain ROI, should be the same sampling as anat
mask=Minc2.crop_volume(
    Minc2.read_volume("mni_icbm152_t1_tal_nlin_sym_09c_mask.mnc",store=UInt8),
    [[15,15],[20,20],[20,20]])

# read statistics map, does not have to be the same resolution as anat
vol_t=Minc2.read_volume("t_AD_vs_CN_2mm.mnc",store=Float64)

# statistical limits (two-tailed)
stat_limits  = [2.9 , 5]

# start new figure
fig = Figure()

g1  = f[1,1] = GridLayout()
Label(f[1,1,Top()],"AD vs CN-")

draw_outline_with_heatmap_symmetric(g1, anat, mask, vol_stat;
    heat_limits=stat_limits,
    show_colorbar=true,
    cmap_pos=:YlOrRd_9,cmap_neg=:YlGnBu_9,
    nslices=5,
    colorbar_label="t-statistics")

resize_to_layout!(fig)

save("t-statistics.png", fig, px_per_unit = 1) 

draw_outline_with_heatmap_symmetric(
    layout, anat, mask, heat; 
    cmap_pos=:YlOrRd_9,
    cmap_neg=:YlGnBu_9,
    levels=[20, 40],
    heat_limits=nothing,
    show_colorbar=true,
    under=nothing, 
    over=nothing,
    nslices=4,
    alpha=0.7,
    colorbar_label="",
    slices_gap=5,
    colorbar_gap=10)