/
0_example_radon_backproject.jl
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/
0_example_radon_backproject.jl
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### A Pluto.jl notebook ###
# v0.19.38
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 $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : iv(el)
el
end
end
# ╔═╡ 4eb3148e-8f8b-11ee-3cfe-854d3bd5cc80
begin
using Pkg
Pkg.activate(".")
Pkg.instantiate()
using Revise
end
# ╔═╡ b336e55e-0be4-422f-b48a-0a2242cb0915
using RadonKA
# ╔═╡ 1311e853-c4cd-42bb-8bf3-5e0d564bf9c5
using IndexFunArrays, ImageShow, Plots, ImageIO, PlutoUI, PlutoTest, TestImages
# ╔═╡ 03bccb92-b47f-477a-9bdb-74cc404da690
using CUDA
# ╔═╡ 6f6c8d28-5a54-440e-9b7a-52e1fce959ab
md"# Load packages
On the first run, Julia is going to install some packages automatically. So start this notebook and give it some minutes to install all packages.
No worries, any future runs will be much faster to start!
"
# ╔═╡ ef92457a-87c0-43bf-a046-9fe82afbbe13
begin
use_CUDA = Ref(true && CUDA.functional())
var"@mytime" = use_CUDA[] ? CUDA.var"@time" : var"@time"
"""
togoc(x)
Stands for "to GPU or CPU". In case you have a GPU, it moves the array to the GPU.
In case CUDA is runable, it will just leave it on the CPU
"""
togoc(x) = use_CUDA[] ? CuArray(x) : x
end
# ╔═╡ f5e2024b-deaf-4344-b610-a4b956abbfaa
md""" ## CUDA
Thanks to Julia multiple dispatch and [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl) our code can run on CUDA GPUs.
Big reconstructions can run 5-20 times faster on a CUDA GPU!
Your CUDA is functional: **$(use_CUDA[])**
"""
# ╔═╡ 810aebe4-2c6e-4ba6-916b-9e4306df33c9
TableOfContents()
# ╔═╡ d25c1381-baf1-429b-8150-622b8f731d83
md"# Example Image"
# ╔═╡ 54208d78-cf55-41d7-b4bf-6d1ab4927bbb
begin
N = 512
N_z = 20
img = box(Float32, (N, N, N_z), (N ÷4, N ÷ 4, 20), offset=(N ÷ 2 + 60, N ÷ 2 -50, N_z ÷ 2)) |> collect
#img = box(Float32, (N, N, N_z), (1, 1, 1)) |> collect
#img = box(Float32, (N, N, N_z), (N ÷2, N ÷ 2, 50), offset=(N ÷ 2 - 50, N ÷ 2 + 50, N_z ÷ 2)) |> collect
img .+= 0.0f0 .+ (rr2(Float32, (N, N, N_z), offset=(180, 210, N_z÷2)) .< 30 .^2)
img[:, :, 1] .= testimage("resolution_test_512")
#img = box(Float32, (100, 100), (3, 3), offset=(51, 51)) |> collect
end;
# ╔═╡ 1393d029-66be-40aa-a2f9-f31317222575
img_c = togoc(img);
# ╔═╡ 8be220a4-293d-411d-bbce-e39b64780814
md"# Radon Transform"
# ╔═╡ b8618268-0892-4abc-ae26-e25e41d07968
angles = range(0f0, 2π, 1000)[begin:end-1]
# ╔═╡ 135e728b-efd8-44bc-81d9-6a2244ce4c31
angles_c = togoc(angles);
# ╔═╡ d2cc6fc6-135b-4c4a-8453-9c5bf9e4a24f
@mytime sinogram = radon(img, angles);
# ╔═╡ dc14103d-993c-402f-a8b5-a35843f3f4ac
@mytime sinogram_c = radon(img_c, angles_c);
# ╔═╡ 783f05e0-2640-4ecd-8c19-1c15a99ee294
@bind i_z Slider(1:size(sinogram, 3), show_value=true)
# ╔═╡ 01b4b8f8-37d5-425f-975e-ebb3890d8624
simshow(img[:, :, i_z])
# ╔═╡ db2676fd-3305-408f-93b4-08a3d04fdd02
@test sinogram ≈ Array(sinogram_c)
# ╔═╡ 1a931e03-6a29-4c3e-b66f-bc1b5936a6f4
simshow(sinogram[:, :, i_z])
# ╔═╡ 3d584d94-b88f-4738-a470-7db1fb3fb996
simshow(Array(sinogram_c[:, :, i_z]))
# ╔═╡ edbf1577-0fd4-4261-bd04-499bc1a0debd
md"# Backproject (adjoint Radon)"
# ╔═╡ 7e27da5a-1b04-4d4c-8c62-eaffa7f4f9ce
@time backproject = RadonKA.backproject(sinogram, angles);
# ╔═╡ 4e367035-eb2f-4dfa-9646-7c182a111c49
md"Use this slider to add more and more angles to the backproject transform"
# ╔═╡ b9bf49a0-7320-4269-9a6a-ac2533ab5fde
@bind angle_limit Slider(1:size(sinogram, 2), default=size(sinogram, 2), show_value=true)
# ╔═╡ 93a7ab4a-b2dc-4fc2-bf69-66e6d615103f
CUDA.@time CUDA.@sync backproject_cu = RadonKA.backproject(sinogram_c[:, begin:angle_limit, :], togoc(angles[begin:angle_limit]));
# ╔═╡ 52a86ed8-4504-4d9e-9ea6-6aeaf8540406
@bind i_z3 Slider(1:size(sinogram, 3), show_value=true)
# ╔═╡ 9d7c41db-adb5-4da2-98ae-96e967c1056e
simshow(Array(backproject_cu[:, :, i_z3]))
# ╔═╡ 81b07387-ede6-4a66-8260-8605cd978ede
md"# Filtered Backprojection"
# ╔═╡ 32b15077-5e09-4693-8f12-3b2029fe63cc
@mytime filtered_bproj = RadonKA.backproject_filtered(sinogram_c, togoc(angles));
# ╔═╡ bc6e2d40-fcd1-4d7b-8f96-3d4d9e4336de
@bind i_z4 Slider(1:size(sinogram, 3), show_value=true)
# ╔═╡ eee184e3-8d5d-42fb-81fb-a5d7e59a083a
simshow(Array(filtered_bproj[:, :, i_z4]))
# ╔═╡ a29be556-174a-4ec5-962d-9fdf203d51aa
backproject ≈ Array(backproject_cu)
# ╔═╡ fd2bab7a-7ef6-42aa-bcb5-2a52bffc61db
# ╔═╡ Cell order:
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