{
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"embedxml"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"using FileIO\n",
"using Plots\n",
"include(\"splitcell.jl\")\n",
"include(\"segmentation3d.jl\")\n",
"include(\"lineage.jl\")\n",
"include(\"normalization3d.jl\")\n",
"include(\"tiffxml.jl\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"d16s1 = load(File(format\"TIFF\", \"../mRNA_confocal_hamamatsu-60X-TIRF/20200316/HE7-11-1-80uw-PWM_1_s1.ome.tiff\"));"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applying LoG(40) at MZJ\n",
"******************************************************************************************************************************************Done\n",
"267.401444 seconds (48.60 M allocations: 64.266 GiB, 12.06% gc time)\n"
]
}
],
"source": [
"@time mask_markers = split_cell_LoG(d16s1, 138);"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applying LoG(40) at MZJ\n",
"******************************************************************************************************************************************Done\n",
"267.401444 seconds (48.60 M allocations: 64.266 GiB, 12.06% gc time)\n"
]
}
],
"source": [
"@time mask_markers = split_cell_LoG(d16s1, 138);"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Finding connected component 98.919461 seconds (6.36 M allocations: 15.463 GiB, 1.15% gc time)\n"
]
},
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"<circle clip-path=\"url(#clip7302)\" cx=\"2032.26\" cy=\"691.416\" r=\"14\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
"<circle clip-path=\"url(#clip7302)\" cx=\"2290.72\" cy=\"766.846\" r=\"14\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
"<path clip-path=\"url(#clip7300)\" d=\"\n",
"M1989.74 251.724 L2280.76 251.724 L2280.76 130.764 L1989.74 130.764 Z\n",
" \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
"<polyline clip-path=\"url(#clip7300)\" style=\"stroke:#000000; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
" 1989.74,251.724 2280.76,251.724 2280.76,130.764 1989.74,130.764 1989.74,251.724 \n",
" \"/>\n",
"<polyline clip-path=\"url(#clip7300)\" style=\"stroke:#009af9; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
" 2013.74,191.244 2157.74,191.244 \n",
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"<path clip-path=\"url(#clip7300)\" d=\"M 0 0 M2195.58 210.931 Q2193.77 215.561 2192.06 216.973 Q2190.35 218.385 2187.48 218.385 L2184.08 218.385 L2184.08 214.82 L2186.58 214.82 Q2188.33 214.82 2189.31 213.987 Q2190.28 213.154 2191.46 210.052 L2192.22 208.107 L2181.74 182.598 L2186.25 182.598 L2194.35 202.876 L2202.46 182.598 L2206.97 182.598 L2195.58 210.931 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip7300)\" d=\"M 0 0 M2212.85 204.589 L2220.49 204.589 L2220.49 178.223 L2212.18 179.89 L2212.18 175.631 L2220.44 173.964 L2225.12 173.964 L2225.12 204.589 L2232.76 204.589 L2232.76 208.524 L2212.85 208.524 L2212.85 204.589 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /></svg>\n"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@time time_line_1, longlived_labels_1, livingtime_1, time_line_whole_1 = find_time_line(mask_markers);\n",
"plot(sum.(livingtime_1), marker=:circle)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Detecting contacted branch\n",
"Found contacted branch: [8, 13]\n",
"Splitting branch 8 now\n",
"Finding connected componentReassigning contacted branch 8 \n",
"Branch 8 -> 100\n",
"Branch 8 -> 101\n",
"Branch 8 -> 102\n",
"Splitting branch 13 now\n",
"Finding connected componentReassigning contacted branch 13 \n",
"169.847874 seconds (6.33 M allocations: 69.349 GiB, 3.73% gc time)\n"
]
}
],
"source": [
"@time split_contacted_cell!(time_line_1, longlived_labels_1, livingtime_1, time_line_whole_1);"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"tracks = walking(time_line_1, longlived_labels_1, livingtime_1);"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Grant domain for each detected cell by watershed\n",
"------------------------------------------------------------------------------------------------------------------------------------------\n",
"Drawing longlived_maps\n",
"-----------[4, 9, 11, 12, 13, 15, 27, 31, 100, 101, 102]\n",
"1243.457421 seconds (3.60 G allocations: 143.098 GiB, 4.24% gc time)\n"
]
}
],
"source": [
"@time d16s1_longlived_maps = grant_domain(d16s1, time_line_1, longlived_labels_1, livingtime_1, time_line_whole_1);"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"102.294139 seconds (1.45 G allocations: 30.045 GiB, 48.39% gc time)\n"
]
}
],
"source": [
"@time cell_1 = pick_cells(d16s1, d16s1_longlived_maps, 1, tracks, longlived_labels_1,\n",
" livingtime_1);"
]
},
{
"cell_type": "code",
"execution_count": 177,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"257×514 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
" Gray{Float64}(0.0) Gray{Float64}(0.0) … Gray{Float64}(0.0)\n",
" Gray{Float64}(0.0) Gray{Float64}(0.0) Gray{Float64}(0.0)\n",
" Gray{Float64}(0.0) Gray{Float64}(0.0) Gray{Float64}(0.0)\n",
" Gray{Float64}(0.0) Gray{Float64}(0.0) Gray{Float64}(0.0)\n",
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"source": [
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"execution_count": 178,
"metadata": {},
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}
],
"source": [
"#img_gs = imfilter(cell_1[128:end-128,128:end-128, 13:14], Kernel.gaussian((2,2,1)))\n",
"plot(leg=false, lw=4)\n",
"yen = []\n",
"for i in 1:20\n",
" img_gs = imfilter(cell_1[128:end-128,128:end-128, i], Kernel.gaussian((4,4)))\n",
" edge, count = build_histogram( img_gs[img_gs.>0.001] )\n",
" push!(yen, otsu_threshold(img_gs[img_gs .> 0.001]) )\n",
" plot!(edge[100:end], count[100:end])\n",
" #plot!([yen, yen], [0, 6000])\n",
"end\n",
"plot!()"
]
},
{
"cell_type": "code",
"execution_count": 180,
"metadata": {},
"outputs": [
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]
},
"execution_count": 180,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"yen_ = median(yen)\n",
"plot!([yen_, yen_], [0, 2000])"
]
},
{
"cell_type": "code",
"execution_count": 182,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting nucleus\n"
]
},
{
"ename": "TaskFailedException",
"evalue": "TaskFailedException:\nInterruptException:\nStacktrace:\n [1] Array at ./boot.jl:409 [inlined]\n [2] Array at ./boot.jl:416 [inlined]\n [3] Array at ./boot.jl:422 [inlined]\n [4] similar at ./abstractarray.jl:671 [inlined]\n [5] similar at ./abstractarray.jl:670 [inlined]\n [6] similar at ./broadcast.jl:196 [inlined]\n [7] copy at ./broadcast.jl:840 [inlined]\n [8] materialize at ./broadcast.jl:820 [inlined]\n [9] macro expansion at /datahub/rawdata/tandeng/mRNA_imaging/CoutingmRNA.jl/segmentation3d.jl:34 [inlined]\n [10] (::var\"#81#threadsfor_fun#6\"{Array{Float64,3},Array{Float64,3},Array{Float64,1},UnitRange{Int64}})(::Bool) at ./threadingconstructs.jl:61\n [11] (::var\"#81#threadsfor_fun#6\"{Array{Float64,3},Array{Float64,3},Array{Float64,1},UnitRange{Int64}})() at ./threadingconstructs.jl:28",
"output_type": "error",
"traceback": [
"TaskFailedException:\nInterruptException:\nStacktrace:\n [1] Array at ./boot.jl:409 [inlined]\n [2] Array at ./boot.jl:416 [inlined]\n [3] Array at ./boot.jl:422 [inlined]\n [4] similar at ./abstractarray.jl:671 [inlined]\n [5] similar at ./abstractarray.jl:670 [inlined]\n [6] similar at ./broadcast.jl:196 [inlined]\n [7] copy at ./broadcast.jl:840 [inlined]\n [8] materialize at ./broadcast.jl:820 [inlined]\n [9] macro expansion at /datahub/rawdata/tandeng/mRNA_imaging/CoutingmRNA.jl/segmentation3d.jl:34 [inlined]\n [10] (::var\"#81#threadsfor_fun#6\"{Array{Float64,3},Array{Float64,3},Array{Float64,1},UnitRange{Int64}})(::Bool) at ./threadingconstructs.jl:61\n [11] (::var\"#81#threadsfor_fun#6\"{Array{Float64,3},Array{Float64,3},Array{Float64,1},UnitRange{Int64}})() at ./threadingconstructs.jl:28",
"",
"Stacktrace:",
" [1] wait(::Task) at ./task.jl:267",
" [2] macro expansion at ./threadingconstructs.jl:69 [inlined]",
" [3] extract3dnucleus(::Array{Float64,3}) at /datahub/rawdata/tandeng/mRNA_imaging/CoutingmRNA.jl/segmentation3d.jl:32",
" [4] macro expansion at ./util.jl:175 [inlined]",
" [5] top-level scope at ./In[182]:1"
]
}
],
"source": [
"@time d16s1_1_nu, d16s1_1_th = extract3dnucleus(cell_1);\n",
"@time save(\"d16s1_1_otsu.tiff\", N0f16.(d16s1_1_nu));\n",
"embedxml(512, 512, 20, 138, \"d16s1_1_otsu_gs.tiff\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 40 threas 1.4.1",
"language": "julia",
"name": "julia-40-threas-1.4"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.4.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
