{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false"
   },
   "source": [
    "# Counte mRNA inside Tracking Cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "Collapsed": "false",
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Precompiling Images [916415d5-f1e6-5110-898d-aaa5f9f070e0]\n",
      "└ @ Base loading.jl:1260\n",
      "WARNING: ImageQualityIndexes.psnr is deprecated, use assess_psnr instead.\n",
      "  likely near /home/hf/.julia/packages/Images/0SDGT/src/Images.jl:60\n",
      "┌ Info: Precompiling ImageSegmentation [80713f31-8817-5129-9cf8-209ff8fb23e1]\n",
      "└ @ Base loading.jl:1260\n",
      "┌ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]\n",
      "└ @ Base loading.jl:1260\n",
      "┌ Info: Precompiling Distributions [31c24e10-a181-5473-b8eb-7969acd0382f]\n",
      "└ @ Base loading.jl:1260\n",
      "┌ Info: Precompiling GaussianMixtures [cc18c42c-b769-54ff-9e2a-b28141a64aae]\n",
      "└ @ Base loading.jl:1260\n"
     ]
    }
   ],
   "source": [
    "using FileIO, Images\n",
    "using ImageSegmentation\n",
    "using Plots\n",
    "using Random\n",
    "using Distributions\n",
    "using GaussianMixtures\n",
    "using Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "get_random_color (generic function with 1 method)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function get_random_color(seed)\n",
    "    Random.seed!(seed)\n",
    "    rand(RGB{N0f8})\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "watershedborder (generic function with 1 method)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Generate border form watershed result\n",
    "\"\"\"\n",
    "#function watershedborder(watershed_segments::SegmentedImage{Array{Int64,2},Float64} )\n",
    "function watershedborder(watershed_segments)\n",
    "    marker_border = BitArray(undef, size(watershed_segments.image_indexmap));\n",
    "    marker_border .=false\n",
    "    #marker_border = zeros(Int8, size(watershed_segments.image_indexmap));\n",
    "    for label in watershed_segments.segment_labels\n",
    "        marker_border .|= ((watershed_segments.image_indexmap.==label) .⊻ erode(watershed_segments.image_indexmap .==label));\n",
    "    end\n",
    "    marker_border;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "data_dir = \"/datahub/rawdata/tandeng/mRNA_imaging/mRNA_confocal_hamamatsu-60X-TIRF\";\n",
    "img_15_1 = load(File(format\"TIFF\", \"$data_dir/20200315/HE7-11-1-80uw-const_1_s1.ome.btf.tiff\"));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "img_16_2 = load(File(format\"TIFF\", \"$data_dir/20200316/HE7-11-1-80uw-PWM_1_s2.ome.tiff\"));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "true"
   },
   "source": [
    "## 1. Distance Tranform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 689,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianDistance (generic function with 2 methods)"
      ]
     },
     "execution_count": 689,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function GaussianDistance(time::Int)\n",
    "\timgout = zeros(N0f16, 1900, 1300, time)\n",
    "    for t in 1:time\n",
    "        imgx = img[:,:,20*t+14];\n",
    "        imgx_th = imfilter(imgx, Kernel.gaussian(9)) .> (140/0xffff);\n",
    "        imgx_dist = distance_transform(feature_transform(imgx_th));\n",
    "        imgx_markers = label_components( imgx_dist .< 10 );\n",
    "        imgx_segments = watershed( imgx_dist, imgx_markers );\n",
    "        #imgx_segments = watershed( imgx_th, imgx_markers);\n",
    "        imgout[:,:,t] = .~watershedborder(imgx_segments) .* imgx;\n",
    "    end\n",
    "    imgout;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 691,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "449.506440 seconds (152.00 k allocations: 51.523 GiB, 7.89% gc time)\n"
     ]
    }
   ],
   "source": [
    "@time gaussian_distance = GaussianDistance(124);\n",
    "save(\"test_1_14.tiff\", gaussian_distance);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "true"
   },
   "source": [
    "# 2. Second method to find suitable marker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 692,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dog (generic function with 1 method)"
      ]
     },
     "execution_count": 692,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function dog(time::Int)\n",
    "    imgout = zeros(N0f16, 1900, 1300, time)\n",
    "    for t in 1:time\n",
    "        imgx = img[:,:,20*t+14];\n",
    "        imgx_th = imfilter(imgx, Kernel.gaussian(11)) .> (140/0xffff);\n",
    "        imgx_dog = imfilter(imgx,Kernel.gaussian(9))-imfilter(imgx,Kernel.gaussian(120))\n",
    "        #[ imgx.*100  imgx_dog.*1000  Gray.(imgx_th) Gray.(imgx_dog.>0.0002)]\n",
    "        imgx_markers = label_components( imgx_dog.>0.0002);\n",
    "        imgx_markers_sl = copy(imgx_markers);\n",
    "        for i in 1:maximum(imgx_markers[:]) \n",
    "            if sum(imgx_markers .== i) < 1e4\n",
    "                imgx_markers_sl = imgx_markers_sl .* (imgx_markers .!=[i])\n",
    "                # remove selected seed\n",
    "            end\n",
    "        end\n",
    "        imgx_segments = watershed( imfilter(1 .- imgx, Kernel.gaussian(9)), imgx_markers_sl);\n",
    "        #[ Gray.(imgx_markers./maximum(imgx_markers[:])) ]\n",
    "        #[ imgx.*100 Gray.(imgx_segments.image_indexmap./length(imgx_segments.segment_labels)) ]\n",
    "        imgout[:,:,t] = .~watershedborder(imgx_segments) .* imgx;\n",
    "    end\n",
    "    imgout;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "function nuclei_gmm(img, watershed_segments::SegmentedImage{Array{Int64,2},Float64})\n",
    "    for label in watershed_segments\n",
    "        edge, counte = imhist(imfilter(img, Kernel.gaussian(7)) .* (watershed_segments.image_indexmap.==label ));\n",
    "    \t#plot(edge[2:end], counte[3:end])\n",
    "        gmm = GMM(3, [i for i in real(imfilter(imgx, Kernel.gaussian(7)) .* (imgx_segments.image_indexmap.==27)) if i>4e-5]);\n",
    "        imgx .* ((imfilter(imgx, Kernel.gaussian(7)) .* (imgx_segments.image_indexmap.==27) ) .> gmm.μ[3]) .*100\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 693,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "720.305134 seconds (282.33 k allocations: 201.867 GiB, 17.52% gc time)\n"
     ]
    }
   ],
   "source": [
    "@time test2_14 = dog(124);\n",
    "save(\"test2_14.tiff\", test2_14);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {
    "Collapsed": "false",
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
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       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:start;\" transform=\"rotate(0, 2181.93, 208.744)\" x=\"2181.93\" y=\"208.744\">y1</text>\n",
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      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marker = [sum(imgx_markers .== i) for i in 1:maximum(imgx_markers) ];\n",
    "histogram(marker, nbins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "metadata": {
    "Collapsed": "false",
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "1900×1300 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.157168)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.16022)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.161746)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.148013)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.155642)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.146487)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.149538)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.155642)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.169375)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.166323)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.158694)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.154116)\n",
       " ⋮                                       ⋱  \n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imgx .* (imgx_segments.image_indexmap.==27) .*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"600\" height=\"400\" viewBox=\"0 0 2400 1600\">\n",
       "<defs>\n",
       "  <clipPath id=\"clip5700\">\n",
       "    <rect x=\"0\" y=\"0\" width=\"2400\" height=\"1600\"/>\n",
       "  </clipPath>\n",
       "</defs>\n",
       "<path clip-path=\"url(#clip5700)\" d=\"\n",
       "M0 1600 L2400 1600 L2400 0 L0 0  Z\n",
       "  \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
       "<defs>\n",
       "  <clipPath id=\"clip5701\">\n",
       "    <rect x=\"480\" y=\"0\" width=\"1681\" height=\"1600\"/>\n",
       "  </clipPath>\n",
       "</defs>\n",
       "<path clip-path=\"url(#clip5700)\" d=\"\n",
       "M247.807 1487.47 L2352.76 1487.47 L2352.76 47.2441 L247.807 47.2441  Z\n",
       "  \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
       "<defs>\n",
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     "execution_count": 379,
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   ],
   "source": [
    "edge, counte = imhist(imfilter(imgx, Kernel.gaussian(7)) .* (imgx_segments.image_indexmap.==27) );\n",
    "plot(edge[2:end], counte[3:end])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {
    "Collapsed": "false",
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Iters               objv        objv-change | affected \n",
      "-------------------------------------------------------------\n",
      "      0       1.512950e-04\n",
      "      1       9.403939e-05      -5.725561e-05 |        3\n",
      "      2       9.128871e-05      -2.750684e-06 |        3\n",
      "      3       9.039588e-05      -8.928299e-07 |        3\n",
      "K-means converged with 3 iterations (objv = 9.03958751673867e-5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Initializing GMM, 3 Gaussians diag covariance 1 dimensions using 516919 data points\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:78\n",
      "┌ Info: K-means with 3000 data points using 3 iterations\n",
      "│ 500.0 data points per parameter\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:139\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n",
      "┌ Warning: Variances had to be floored \n",
      "│   ind = [1, 2, 3]\n",
      "└ @ GaussianMixtures /home/hf/.julia/packages/GaussianMixtures/3jRIL/src/train.jl:258\n"
     ]
    }
   ],
   "source": [
    "gmm = GMM(3, [i for i in real(imfilter(imgx, Kernel.gaussian(7)) .* (imgx_segments.image_indexmap.==27)) if i>4e-5]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3×2 Array{Float64,2}:\n",
       " 0.00179465  0.736267\n",
       " 0.00379739  0.0584128\n",
       " 0.00200267  0.20532"
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     },
     "execution_count": 381,
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   ],
   "source": [
    "[gmm.μ gmm.w]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {
    "Collapsed": "false"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "MixtureModel{Normal{Float64}}(K = 3)\n",
       "components[1] (prior = 0.7363): Normal{Float64}(μ=0.001794645191997088, σ=9.387936253366946e-9)\n",
       "components[2] (prior = 0.0584): Normal{Float64}(μ=0.003797385783700723, σ=3.2003100792516977e-7)\n",
       "components[3] (prior = 0.2053): Normal{Float64}(μ=0.002002669744912961, σ=4.2954883850133567e-8)\n"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gmm_mm = MixtureModel(gmm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {
    "Collapsed": "false",
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "1900×1300 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " ⋮                                       ⋱  \n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)  …  Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)\n",
       " Gray{Float32}(0.0)  Gray{Float32}(0.0)     Gray{Float32}(0.0)"
      ]
     },
     "execution_count": 384,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imgx .* ((imfilter(imgx, Kernel.gaussian(7)) .* (imgx_segments.image_indexmap.==27) ) .> gmm.μ[3]) .*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false"
   },
   "source": [
    "# 3. LoG, Distance Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "split_cell_LoG"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Use LoG and Distance Map fiter raw image to extract cell\n",
    "\"\"\"\n",
    "function LoGDistance(time)\n",
    "    imgout = zeros(N0f16, 1900, 1300, time)\n",
    "    for i in 1:time\n",
    "        imgx = img[:, :, 20*i+14];\n",
    "        imgx_log = imfilter(imgx, Kernel.LoG(40)) .< -1e-7 ;\n",
    "        imgx_dist = distance_transform(feature_transform(imgx_log)) .^ 0.5;\n",
    "        imgx_markers = label_components( imgx_dist .< 5);\n",
    "        #imgx_segments = watershed( imgx_dist, imgx_markers);  \n",
    "        #imgx_segments = watershed( imgx, imgx_markers);\n",
    "        imgout[:,:,i] = .~watershedborder(imgx_segments).*imgx;\n",
    "    end\n",
    "\t#map(i->get_random_color(i),labels_map(imgx_segments))]\n",
    "    imgout\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Use LoG without Distance Map fiter raw image to extract cell\n",
    "\"\"\"\n",
    "function split_cell_LoG(stack::Array{Gray{Normed{UInt16,16}},3}, time::Int)\n",
    "    img_edge = zeros(N0f16, 1900, 1300, time);\n",
    "    img_clear = zeros(N0f16, 1900, 1300, time);\n",
    "    for i in 1:time\n",
    "        imgx = mapwindow(median!, stack[:, :, 20*i+14], (5,5));\n",
    "        imgx_log = imfilter(imgx, Kernel.LoG(40)) .< -1e-7 ;\n",
    "        imgx_dist = distance_transform(feature_transform(imgx_log)) .^ 0.5;\n",
    "        imgx_markers = label_components( imgx_dist .< 5);\n",
    "        #imgx_segments = watershed( imgx_dist, imgx_markers);  \n",
    "        imgx_segments = watershed( imfilter(1 .- imgx, Kernel.gaussian(9)), imgx_markers);\n",
    "        #imgout[:,:,i] = Gray.(imgx_segments.image_indexmap./maximum(imgx_segments.segment_labels));\n",
    "        img_edge[:,:,i] = .~watershedborder(imgx_segments).*imgx;\n",
    "        img_clear[:,:,i] = extract_nucleus( imgx, imgx_segments);\n",
    "    end\n",
    "\t#map(i->get_random_color(i),labels_map(imgx_segments))]\n",
    "    img_edge, img_clear;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "split_cell_LoG"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Use LoG without Distance Map fiter raw image to extract cell\n",
    "\"\"\"\n",
    "function split_cell_LoG(stack::Array{Gray{Normed{UInt16,16}},3}, time::Int)\n",
    "    img_edge = zeros(N0f16, 1900, 1300, time);\n",
    "    img_clear = zeros(N0f16, 1900, 1300, time*20);\n",
    "    for i in 1:time\n",
    "        imgx = mapwindow(median!, stack[:, :, 20*i+14], (5,5));\n",
    "        imgx_log = imfilter(imgx, Kernel.LoG(40)) .< -1e-7 ;\n",
    "        imgx_dist = distance_transform(feature_transform(imgx_log)) .^ 0.5;\n",
    "        imgx_markers = label_components( imgx_dist .< 5);\n",
    "        #imgx_segments = watershed( imgx_dist, imgx_markers);  \n",
    "        imgx_segments = watershed( imfilter(1 .- imgx, Kernel.gaussian(9)), imgx_markers);\n",
    "        #imgout[:,:,i] = Gray.(imgx_segments.image_indexmap./maximum(imgx_segments.segment_labels));\n",
    "        img_edge[:,:,i] = .~watershedborder(imgx_segments).*imgx;\n",
    "        img_clear_mask = extract_nucleus( imgx, imgx_segments) .> 0;\n",
    "        for z in 1:20\n",
    "            img_clear[:,:,(i-1)*20+z] = img_clear_mask .* stack[:,:,(i-1)*20+z]\n",
    "        end\n",
    "    end\n",
    "\t#map(i->get_random_color(i),labels_map(imgx_segments))]\n",
    "    img_edge, img_clear;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "split_cell_LoG"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Use LoG without Distance Map fiter raw image to extract cell, \n",
    "\"\"\"\n",
    "function split_cell_LoG(stack::Array{Gray{Normed{UInt16,16}},3}, time::Int)\n",
    "    img_edge = zeros(N0f16, 1900, 1300, time);\n",
    "    img_clear = zeros(N0f16, 1900, 1300, time*20);\n",
    "    for i in 1:time\n",
    "        imgx = mapwindow(median!, stack[:, :, 20*i+14], (5,5));\n",
    "        imgx_log = imfilter(imgx, Kernel.LoG(40)) .< -1e-7 ;\n",
    "        imgx_dist = distance_transform(feature_transform(imgx_log)) .^ 0.5;\n",
    "        imgx_markers = label_components( imgx_dist .< 5);\n",
    "        #imgx_segments = watershed( imgx_dist, imgx_markers);  \n",
    "        imgx_segments = watershed( imfilter(1 .- imgx, Kernel.gaussian(9)), imgx_markers);\n",
    "        #imgout[:,:,i] = Gray.(imgx_segments.image_indexmap./maximum(imgx_segments.segment_labels));\n",
    "        img_edge[:,:,i] = .~watershedborder(imgx_segments).*imgx;\n",
    "        img_clear_mask = extract_nucleus( imgx, imgx_segments) .> 0;\n",
    "        for z in 1:20\n",
    "            img_clear[:,:,(i-1)*20+z] = img_clear_mask .* stack[:,:,(i-1)*20+z]\n",
    "        end\n",
    "    end\n",
    "\t#map(i->get_random_color(i),labels_map(imgx_segments))]\n",
    "    img_edge, img_clear;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "extract_nucleus"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Extract nucleus from sperated cell\n",
    "\"\"\"\n",
    "function extract_nucleus( img, watershed_segments::SegmentedImage{Array{Int64,2},Float64} )\n",
    "    img_clear = zeros(N0f16, size(watershed_segments.image_indexmap));\n",
    "    img_blur = imfilter(img, Kernel.gaussian(9));\n",
    "    for label in watershed_segments.segment_labels\n",
    "        cell = img_blur .* (watershed_segments.image_indexmap .== label);\n",
    "        # only select 70% brigter region or fixed area\n",
    "        gmm = GMM(3, [pixel for pixel in real(cell) if pixel > 1e-5]);\n",
    "        nucleus_th = sort(gmm.μ, dims=1)[end-1];\n",
    "        img_clear .+= ( remove_small_area(cell .> nucleus_th)) .*img;\n",
    "    end\n",
    "    img_clear;\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Just remove regions are small\n",
    "\"\"\"\n",
    "function remove_small_area(mask)\n",
    "    mask_con = label_components(mask);\n",
    "    mask_res = BitArray(undef, size(mask));\n",
    "    mask_res .= false;cd\n",
    "    for i in 1:maximum(mask_con)\n",
    "        if sum(mask_con .== i) > 5e3\n",
    "            mask_res .+= (mask_con.==i);\n",
    "        end\n",
    "    end\n",
    "    mask_res;\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "Collapsed": "false",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "@time edge, clear = split_cell_LoG(img_15_1, 20);\n",
    "save(\"output/img_15_1_edge.tiff\", edge);\n",
    "save(\"output/img_15_1_clear.tiff\", clear);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "Collapsed": "false",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "@time edge, clear = split_cell_LoG(img_16_2, 20);\n",
    "save(\"output/img_16_2_edge_z.tiff\", edge);\n",
    "save(\"output/img_16_2_clear_z.tiff\", clear);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "Collapsed": "false",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "@time out = split_cell_LoG(img_16_2, 137);\n",
    "save(\"output/img_16_2.tiff\", out);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "1900×2600 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
       " Gray{Float32}(0.146487)  Gray{Float32}(0.155642)  …  Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.157168)  Gray{Float32}(0.163272)     Gray{Float32}(0.155642)\n",
       " Gray{Float32}(0.169375)  Gray{Float32}(0.164797)     Gray{Float32}(0.155642)\n",
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       " Gray{Float32}(0.158694)  Gray{Float32}(0.151064)     Gray{Float32}(0.155642)\n",
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       " Gray{Float32}(0.167849)  Gray{Float32}(0.158694)  …  Gray{Float32}(0.15259)\n",
       " Gray{Float32}(0.164797)  Gray{Float32}(0.175479)     Gray{Float32}(0.15259)\n",
       " Gray{Float32}(0.151064)  Gray{Float32}(0.166323)     Gray{Float32}(0.15259)\n",
       " ⋮                                                 ⋱  \n",
       " Gray{Float32}(0.233463)  Gray{Float32}(0.210575)     Gray{Float32}(0.157168)\n",
       " Gray{Float32}(0.244144)  Gray{Float32}(0.215152)     Gray{Float32}(0.157168)\n",
       " Gray{Float32}(0.189212)  Gray{Float32}(0.228885)  …  Gray{Float32}(0.157168)\n",
       " Gray{Float32}(0.215152)  Gray{Float32}(0.19379)      Gray{Float32}(0.155642)\n",
       " Gray{Float32}(0.262455)  Gray{Float32}(0.190738)     Gray{Float32}(0.158694)\n",
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       " Gray{Float32}(0.221256)  Gray{Float32}(0.222782)  …  Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.242618)  Gray{Float32}(0.228885)     Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.201419)  Gray{Float32}(0.201419)     Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.178531)  Gray{Float32}(0.216678)     Gray{Float32}(0.154116)\n",
       " Gray{Float32}(0.172427)  Gray{Float32}(0.213626)     Gray{Float32}(0.154116)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[img_15_1[:,:,10].*100 mapwindow(median!, img_15_1[:,:,10], (5,5)).*100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [
    {
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       "  716.723,1435.9 721.788,1426.2 726.853,1435.91 731.917,1436.33 736.982,1426.47 742.047,1436.5 747.111,1436.4 752.176,1436.86 757.241,1428.14 762.305,1437.38 \n",
       "  767.37,1437.4 772.435,1428.8 777.499,1437.71 782.564,1438.18 787.628,1429.92 792.693,1438.2 797.758,1437.89 802.822,1430.07 807.887,1438.32 812.952,1438.4 \n",
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      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n",
      "GKS: character ignored due to unicode error\n"
     ]
    }
   ],
   "source": [
    "edges, count = imhist(img_15_1[:,:,11]); \n",
    "edges2, count2 = imhist(mapwindow(median!, img_15_1[:,:,0], (5,5)));\n",
    "edges3, count3 = imhist(imfilter(img_15_1[:,:,10], Kernel.gaussian(3)));\n",
    "gr()\n",
    "plot(edges, count[2:end], label=\"raw\");\n",
    "plot!(edges2, count2[2:end], label=\"median\")\n",
    "plot!(edges3, count3[2:end], label=\"gaussian\")"
   ]
  }
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