EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "import os\n",
    "import nibabel as nib\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Load the .nii files in the folder\n",
    "files = glob.glob('./data/**/*.nii',recursive=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#put all the image files in a dictionary\n",
    "imageFiles = {file.split('/')[2]:[] for file in files}\n",
    "for file in files:\n",
    "    imageFiles[file.split('/')[2]].append(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "patientDF=pd.DataFrame(columns=['ID:No','DWI Max','DWI Min','Flair Max','Flair Min','T1 Max','T1 Min','T2 Max','T2 Min','X Shape','Y Shape','Z Shape'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients=sorted([int(x) for x in list(imageFiles.keys())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "for idno in patients:\n",
    "    dataframe = []\n",
    "    dataframe.append(int(idno))\n",
    "    for file in sorted(imageFiles[str(idno)])[:-1]:\n",
    "        img = nib.load(file).get_fdata()\n",
    "        dataframe.append(img.max())\n",
    "        dataframe.append(img.min())\n",
    "    dataframe.append(img.shape[0])\n",
    "    dataframe.append(img.shape[1])\n",
    "    dataframe.append(img.shape[2])\n",
    "    patientDF.loc[len(patientDF)]=dataframe\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID:No</th>\n",
       "      <th>DWI Max</th>\n",
       "      <th>DWI Min</th>\n",
       "      <th>Flair Max</th>\n",
       "      <th>Flair Min</th>\n",
       "      <th>T1 Max</th>\n",
       "      <th>T1 Min</th>\n",
       "      <th>T2 Max</th>\n",
       "      <th>T2 Min</th>\n",
       "      <th>X Shape</th>\n",
       "      <th>Y Shape</th>\n",
       "      <th>Z Shape</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1769.795654</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1825.642212</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2535.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3088.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1917.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1819.262207</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3390.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2678.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2153.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1871.432007</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2506.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2511.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1802.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1762.470337</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2305.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2893.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2232.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1295.686523</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2608.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2556.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>2281.177002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1442.577515</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2201.418945</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2429.456787</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1891.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1788.575439</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4741.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2702.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.0</td>\n",
       "      <td>1825.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1623.515015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3525.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1979.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.0</td>\n",
       "      <td>433.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>401.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>282.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>570.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.0</td>\n",
       "      <td>420.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>643.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>241.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>602.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11.0</td>\n",
       "      <td>1171.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1433.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1080.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1422.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12.0</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>354.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>264.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>494.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13.0</td>\n",
       "      <td>444.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>406.000000</td>\n",
       "      <td>-41.0</td>\n",
       "      <td>221.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>522.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14.0</td>\n",
       "      <td>617.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>401.000000</td>\n",
       "      <td>-48.0</td>\n",
       "      <td>265.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>548.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15.0</td>\n",
       "      <td>529.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>474.000000</td>\n",
       "      <td>-34.0</td>\n",
       "      <td>286.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16.0</td>\n",
       "      <td>391.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>436.000000</td>\n",
       "      <td>-37.0</td>\n",
       "      <td>304.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>596.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17.0</td>\n",
       "      <td>394.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>383.000000</td>\n",
       "      <td>-36.0</td>\n",
       "      <td>232.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>476.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18.0</td>\n",
       "      <td>403.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>425.000000</td>\n",
       "      <td>-33.0</td>\n",
       "      <td>279.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>523.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19.0</td>\n",
       "      <td>531.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>447.000000</td>\n",
       "      <td>-31.0</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>502.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20.0</td>\n",
       "      <td>520.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>439.000000</td>\n",
       "      <td>-37.0</td>\n",
       "      <td>308.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>635.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21.0</td>\n",
       "      <td>427.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>566.000000</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>348.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22.0</td>\n",
       "      <td>474.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>566.000000</td>\n",
       "      <td>-42.0</td>\n",
       "      <td>312.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>602.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23.0</td>\n",
       "      <td>609.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>-35.0</td>\n",
       "      <td>259.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>567.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24.0</td>\n",
       "      <td>390.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>397.000000</td>\n",
       "      <td>-33.0</td>\n",
       "      <td>244.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>456.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25.0</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>397.000000</td>\n",
       "      <td>-39.0</td>\n",
       "      <td>235.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>503.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26.0</td>\n",
       "      <td>353.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>436.000000</td>\n",
       "      <td>-27.0</td>\n",
       "      <td>261.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>521.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27.0</td>\n",
       "      <td>333.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>470.000000</td>\n",
       "      <td>-44.0</td>\n",
       "      <td>327.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>681.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28.0</td>\n",
       "      <td>470.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.000000</td>\n",
       "      <td>-45.0</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>590.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID:No      DWI Max  DWI Min    Flair Max  Flair Min       T1 Max  T1 Min  \\\n",
       "0     1.0  1769.795654      0.0  1825.642212        0.0  2535.000000     0.0   \n",
       "1     2.0  1917.000000      0.0  1819.262207        0.0  3390.000000     0.0   \n",
       "2     3.0  2153.000000      0.0  1871.432007        0.0  2506.000000     0.0   \n",
       "3     4.0  1802.000000      0.0  1762.470337        0.0  2305.000000     0.0   \n",
       "4     5.0  2232.000000      0.0  1295.686523        0.0  2608.000000     0.0   \n",
       "5     6.0  2281.177002      0.0  1442.577515        0.0  2201.418945     0.0   \n",
       "6     7.0  1891.000000      0.0  1788.575439        0.0  4741.000000     0.0   \n",
       "7     8.0  1825.000000      0.0  1623.515015        0.0  3525.000000     0.0   \n",
       "8     9.0   433.000000      0.0   401.000000        0.0   282.000000     0.0   \n",
       "9    10.0   420.000000      0.0   643.000000        0.0   241.000000     0.0   \n",
       "10   11.0  1171.000000      0.0  1433.000000        0.0  1080.000000     0.0   \n",
       "11   12.0   399.000000      0.0   354.000000        0.0   264.000000     0.0   \n",
       "12   13.0   444.000000      0.0   406.000000      -41.0   221.000000     0.0   \n",
       "13   14.0   617.000000      0.0   401.000000      -48.0   265.000000     0.0   \n",
       "14   15.0   529.000000      0.0   474.000000      -34.0   286.000000     0.0   \n",
       "15   16.0   391.000000      0.0   436.000000      -37.0   304.000000     0.0   \n",
       "16   17.0   394.000000      0.0   383.000000      -36.0   232.000000     0.0   \n",
       "17   18.0   403.000000      0.0   425.000000      -33.0   279.000000     0.0   \n",
       "18   19.0   531.000000      0.0   447.000000      -31.0   230.000000     0.0   \n",
       "19   20.0   520.000000      0.0   439.000000      -37.0   308.000000     0.0   \n",
       "20   21.0   427.000000      0.0   566.000000      -45.0   348.000000     0.0   \n",
       "21   22.0   474.000000      0.0   566.000000      -42.0   312.000000     0.0   \n",
       "22   23.0   609.000000      0.0   409.000000      -35.0   259.000000     0.0   \n",
       "23   24.0   390.000000      0.0   397.000000      -33.0   244.000000     0.0   \n",
       "24   25.0   547.000000      0.0   397.000000      -39.0   235.000000     0.0   \n",
       "25   26.0   353.000000      0.0   436.000000      -27.0   261.000000     0.0   \n",
       "26   27.0   333.000000      0.0   470.000000      -44.0   327.000000     0.0   \n",
       "27   28.0   470.000000      0.0   477.000000      -45.0   297.000000     0.0   \n",
       "\n",
       "         T2 Max  T2 Min  X Shape  Y Shape  Z Shape  \n",
       "0   3088.000000     0.0    230.0    230.0    154.0  \n",
       "1   2678.000000     0.0    230.0    230.0    154.0  \n",
       "2   2511.000000     0.0    230.0    230.0    154.0  \n",
       "3   2893.000000     0.0    230.0    230.0    153.0  \n",
       "4   2556.000000     0.0    230.0    230.0    154.0  \n",
       "5   2429.456787     0.0    230.0    230.0    154.0  \n",
       "6   2702.000000     0.0    230.0    230.0    154.0  \n",
       "7   1979.000000     0.0    230.0    230.0    153.0  \n",
       "8    570.000000     0.0    230.0    230.0    153.0  \n",
       "9    602.000000     0.0    230.0    230.0    153.0  \n",
       "10  1422.000000     0.0    230.0    230.0    154.0  \n",
       "11   494.000000     0.0    230.0    230.0    154.0  \n",
       "12   522.000000     0.0    230.0    230.0    153.0  \n",
       "13   548.000000     0.0    230.0    230.0    153.0  \n",
       "14   547.000000     0.0    230.0    230.0    154.0  \n",
       "15   596.000000     0.0    230.0    230.0    154.0  \n",
       "16   476.000000     0.0    230.0    230.0    153.0  \n",
       "17   523.000000     0.0    230.0    230.0    154.0  \n",
       "18   502.000000     0.0    230.0    230.0    154.0  \n",
       "19   635.000000     0.0    230.0    230.0    154.0  \n",
       "20   604.000000     0.0    230.0    230.0    153.0  \n",
       "21   602.000000     0.0    230.0    230.0    153.0  \n",
       "22   567.000000     0.0    230.0    230.0    154.0  \n",
       "23   456.000000     0.0    230.0    230.0    153.0  \n",
       "24   503.000000     0.0    230.0    230.0    153.0  \n",
       "25   521.000000     0.0    230.0    230.0    153.0  \n",
       "26   681.000000     0.0    230.0    230.0    154.0  \n",
       "27   590.000000     0.0    230.0    230.0    154.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patientDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getDetails(imageFiles):\n",
    "    patientDF=pd.DataFrame(columns=['patient','Grey Matter Volume', 'Stroke Volume', 'percentage affected'])\n",
    "    patients=sorted([int(x) for x in list(imageFiles.keys())])\n",
    "    for patient in patients:\n",
    "        \n",
    "        scanPath=sorted(imageFiles[str(patient)])[-2]\n",
    "        scan=nib.load(scanPath).get_fdata()\n",
    "        \n",
    "        # normalise \n",
    "        scan-=scan.min()\n",
    "        scan/=scan.max()\n",
    "        \n",
    "        # count all non zeros values get brain values\n",
    "        greyMatterVolume=np.count_nonzero(scan)\n",
    "        annotPath=sorted(imageFiles[str(patient)])[-1]\n",
    "        \n",
    "        annot=nib.load(annotPath).get_fdata()\n",
    "        \n",
    "        # count all non zeros values get storke values\n",
    "        strokeVolume=np.count_nonzero(annot)\n",
    "\n",
    "        entry=[patient,greyMatterVolume,strokeVolume,(strokeVolume/greyMatterVolume)*100]\n",
    "        \n",
    "        patientDF.loc[len(patientDF)]=entry\n",
    "    \n",
    "    return patientDF     \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "StrokeDF=getDetails(imageFiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>patient</th>\n",
       "      <th>Grey Matter Volume</th>\n",
       "      <th>Stroke Volume</th>\n",
       "      <th>percentage affected</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1383508.0</td>\n",
       "      <td>140657.0</td>\n",
       "      <td>10.166692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1329390.0</td>\n",
       "      <td>32466.0</td>\n",
       "      <td>2.442173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1145120.0</td>\n",
       "      <td>4144.0</td>\n",
       "      <td>0.361883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1658136.0</td>\n",
       "      <td>233547.0</td>\n",
       "      <td>14.084912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1327508.0</td>\n",
       "      <td>100066.0</td>\n",
       "      <td>7.537883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1243793.0</td>\n",
       "      <td>91443.0</td>\n",
       "      <td>7.351947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1454973.0</td>\n",
       "      <td>86603.0</td>\n",
       "      <td>5.952207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.0</td>\n",
       "      <td>1593941.0</td>\n",
       "      <td>29581.0</td>\n",
       "      <td>1.855840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.0</td>\n",
       "      <td>1862078.0</td>\n",
       "      <td>162530.0</td>\n",
       "      <td>8.728421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.0</td>\n",
       "      <td>1356619.0</td>\n",
       "      <td>89853.0</td>\n",
       "      <td>6.623304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11.0</td>\n",
       "      <td>1310214.0</td>\n",
       "      <td>20104.0</td>\n",
       "      <td>1.534406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12.0</td>\n",
       "      <td>1488939.0</td>\n",
       "      <td>21273.0</td>\n",
       "      <td>1.428735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13.0</td>\n",
       "      <td>1592174.0</td>\n",
       "      <td>4858.0</td>\n",
       "      <td>0.305117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14.0</td>\n",
       "      <td>1670399.0</td>\n",
       "      <td>117956.0</td>\n",
       "      <td>7.061546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15.0</td>\n",
       "      <td>1580435.0</td>\n",
       "      <td>29842.0</td>\n",
       "      <td>1.888214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16.0</td>\n",
       "      <td>1450320.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>0.026408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17.0</td>\n",
       "      <td>1503658.0</td>\n",
       "      <td>3373.0</td>\n",
       "      <td>0.224320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18.0</td>\n",
       "      <td>1527213.0</td>\n",
       "      <td>14280.0</td>\n",
       "      <td>0.935037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19.0</td>\n",
       "      <td>1494724.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>0.041279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20.0</td>\n",
       "      <td>1658463.0</td>\n",
       "      <td>23946.0</td>\n",
       "      <td>1.443867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21.0</td>\n",
       "      <td>1519657.0</td>\n",
       "      <td>579.0</td>\n",
       "      <td>0.038101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22.0</td>\n",
       "      <td>1738598.0</td>\n",
       "      <td>9549.0</td>\n",
       "      <td>0.549236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23.0</td>\n",
       "      <td>1511205.0</td>\n",
       "      <td>1378.0</td>\n",
       "      <td>0.091186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24.0</td>\n",
       "      <td>1409135.0</td>\n",
       "      <td>2678.0</td>\n",
       "      <td>0.190046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25.0</td>\n",
       "      <td>1593333.0</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>0.125649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26.0</td>\n",
       "      <td>1636725.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>0.026944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27.0</td>\n",
       "      <td>1429555.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>0.007415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28.0</td>\n",
       "      <td>1639656.0</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>0.122221</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    patient  Grey Matter Volume  Stroke Volume  percentage affected\n",
       "0       1.0           1383508.0       140657.0            10.166692\n",
       "1       2.0           1329390.0        32466.0             2.442173\n",
       "2       3.0           1145120.0         4144.0             0.361883\n",
       "3       4.0           1658136.0       233547.0            14.084912\n",
       "4       5.0           1327508.0       100066.0             7.537883\n",
       "5       6.0           1243793.0        91443.0             7.351947\n",
       "6       7.0           1454973.0        86603.0             5.952207\n",
       "7       8.0           1593941.0        29581.0             1.855840\n",
       "8       9.0           1862078.0       162530.0             8.728421\n",
       "9      10.0           1356619.0        89853.0             6.623304\n",
       "10     11.0           1310214.0        20104.0             1.534406\n",
       "11     12.0           1488939.0        21273.0             1.428735\n",
       "12     13.0           1592174.0         4858.0             0.305117\n",
       "13     14.0           1670399.0       117956.0             7.061546\n",
       "14     15.0           1580435.0        29842.0             1.888214\n",
       "15     16.0           1450320.0          383.0             0.026408\n",
       "16     17.0           1503658.0         3373.0             0.224320\n",
       "17     18.0           1527213.0        14280.0             0.935037\n",
       "18     19.0           1494724.0          617.0             0.041279\n",
       "19     20.0           1658463.0        23946.0             1.443867\n",
       "20     21.0           1519657.0          579.0             0.038101\n",
       "21     22.0           1738598.0         9549.0             0.549236\n",
       "22     23.0           1511205.0         1378.0             0.091186\n",
       "23     24.0           1409135.0         2678.0             0.190046\n",
       "24     25.0           1593333.0         2002.0             0.125649\n",
       "25     26.0           1636725.0          441.0             0.026944\n",
       "26     27.0           1429555.0          106.0             0.007415\n",
       "27     28.0           1639656.0         2004.0             0.122221"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "StrokeDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualizeStroke(view,images=5):\n",
    "    path='./dataPreprocessed/'+view\n",
    "    \n",
    "    views=['sagital','frontal','coronal']\n",
    "    files=glob.glob(path+'/*_*')\n",
    "    files+=[path+'/annot']\n",
    "    # load the modalities for the view\n",
    "    listScans=[np.load(file,allow_pickle=True) for file in files]\n",
    "    \n",
    "    ## get random locations to display\n",
    "    randomLoc=np.random.randint(listScans[0].shape[views.index(view)], size=images)\n",
    "    \n",
    "    for loc in randomLoc:\n",
    "        fig=plt.figure(figsize=(20,5))\n",
    "        seg=listScans[-1]\n",
    "        for i, img in enumerate(listScans[:-1]):\n",
    "            plt.subplot(1,4,i+1)\n",
    "            plt.title(files[i].split('/')[-1])\n",
    "            if view=='coronal':\n",
    "                # plot the image\n",
    "                plt.imshow(np.rot90(img[:,:,loc]),cmap='gray')\n",
    "                # overlay the segmentation mask\n",
    "                plt.imshow(np.rot90(seg[:,:,loc]),alpha=0.4,cmap='Blues')\n",
    "            elif view=='sagital':\n",
    "                # plot the image\n",
    "                plt.imshow(np.rot90(img[loc,:,:]),cmap='gray')\n",
    "                # overlay the segmentation mask\n",
    "                plt.imshow(np.rot90(seg[loc,:,:]),alpha=0.4,cmap='Blues')\n",
    "            elif view=='frontal':\n",
    "                # plot the image\n",
    "                plt.imshow(np.rot90(img[:,loc,:]),cmap='gray')\n",
    "                # overlay the segmentation mask\n",
    "                plt.imshow(np.rot90(seg[:,loc,:]),alpha=0.4,cmap='Blues')\n",
    "                \n",
    "\n",
    "            plt.axis('off')\n",
    "        plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualizeStroke('coronal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}