statistical_analysis_of_validation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "path_summary_json = '/media/immersive/KINGSTON/nnUnetData-and-Models/dataset/nnUNet_trained_models/Dataset116_small_tumors_MRI_lighter/nnUNetTrainerDiceTopK10Loss__nnUNetPlans__3d_lowres/fold_all/summary.json'\n",
    "path_dataset_info_csv = '/media/immersive/KINGSTON/Breast-MRI-Dataset/data_sorted_by_size.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path_summary_json) as json_file:\n",
    "    data_validation = json.load(json_file)\n",
    "\n",
    "df_val = pd.DataFrame(columns= ['Subject ID', 'Tumor volume (voxels)', 'Tumor size [mm]' , 'TP', 'TN', 'FP', 'FN', 'Dice', 'PPV', 'TPR'])\n",
    "# PPV = Precision, TPR = Sensitivity = Recall\n",
    "\n",
    "median_volume = 1.0*176 *0.7031*490 * 0.7031*505       # [mm^3]\n",
    "median_volume_per_voxel = median_volume / (176*490*505) # [mm^3/voxel]\n",
    "\n",
    "for subject in data_validation['metric_per_case']:\n",
    "    pred_file = subject['reference_file']\n",
    "    metrics = subject['metrics']['1']\n",
    "    tp, tn, fp, fn = metrics['TP'], metrics['TN'], metrics['FP'], metrics['FN']\n",
    "    vol = tp + fn\n",
    "    size = (vol * median_volume_per_voxel) ** (1/3)     # [mm]\n",
    "    dc = metrics['Dice']\n",
    "    ppv = tp / (tp + fp) if tp + fp != 0 else 0\n",
    "    tpr = tp / (tp + fn) if tp + fn != 0 else 0\n",
    "    id = pred_file.split('/')[-1].split('.')[0]\n",
    "    row = pd.DataFrame({'Subject ID': [id], 'Tumor volume (voxels)': [vol], 'Tumor size [mm]': [size], 'TP': [tp], 'TN': [tn], 'FP': [fp], 'FN': [fn], 'Dice': [dc], 'PPV': [ppv], 'TPR': [tpr]})\n",
    "\n",
    "    df_val = pd.concat([df_val, row], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Subject ID</th>\n",
       "      <th>Tumor volume (voxels)</th>\n",
       "      <th>Tumor size [mm]</th>\n",
       "      <th>TP</th>\n",
       "      <th>TN</th>\n",
       "      <th>FP</th>\n",
       "      <th>FN</th>\n",
       "      <th>Dice</th>\n",
       "      <th>PPV</th>\n",
       "      <th>TPR</th>\n",
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       "      <th>178</th>\n",
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       "      <td>3070</td>\n",
       "      <td>38792486</td>\n",
       "      <td>212</td>\n",
       "      <td>1544</td>\n",
       "      <td>0.777609</td>\n",
       "      <td>0.935405</td>\n",
       "      <td>0.665366</td>\n",
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       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>0916</td>\n",
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       "      <td>3026</td>\n",
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       "      <td>442</td>\n",
       "      <td>1611</td>\n",
       "      <td>0.746700</td>\n",
       "      <td>0.872549</td>\n",
       "      <td>0.652577</td>\n",
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       "      <td>796</td>\n",
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       "      <td>0.962515</td>\n",
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      ],
      "text/plain": [
       "    Subject ID Tumor volume (voxels)  Tumor size [mm]    TP        TN    FP  \\\n",
       "234       0889                    44         2.791444     0  40893742   678   \n",
       "156       0580                    45         2.812433     0  38534442   681   \n",
       "88        0336                    45         2.812433     0  44039540   607   \n",
       "108       0396                    57         3.043007     0  33030087     0   \n",
       "229       0855                    80         3.407020     0  44038505  1607   \n",
       "..         ...                   ...              ...   ...       ...   ...   \n",
       "178       0670                  4614        13.163476  3070  38792486   212   \n",
       "243       0916                  4637        13.185313  3026  41413673   442   \n",
       "61        0235                  5094        13.604974  2352  44034521   577   \n",
       "33        0126                  6561        14.802489   796  32106048    31   \n",
       "35        0129                  7038        15.152856   134  49273393  2641   \n",
       "\n",
       "       FN      Dice       PPV       TPR  \n",
       "234    44  0.000000  0.000000  0.000000  \n",
       "156    45  0.000000  0.000000  0.000000  \n",
       "88     45  0.000000  0.000000  0.000000  \n",
       "108    57  0.000000  0.000000  0.000000  \n",
       "229    80  0.000000  0.000000  0.000000  \n",
       "..    ...       ...       ...       ...  \n",
       "178  1544  0.777609  0.935405  0.665366  \n",
       "243  1611  0.746700  0.872549  0.652577  \n",
       "61   2742  0.586314  0.803004  0.461720  \n",
       "33   5765  0.215485  0.962515  0.121323  \n",
       "35   6904  0.027311  0.048288  0.019039  \n",
       "\n",
       "[247 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort by tumor volume\n",
    "df_val = df_val.sort_values(by=['Tumor volume (voxels)'], ascending=True)\n",
    "# pd.set_option('display.max_rows', None)       # Show whole df_val\n",
    "df_val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median Dice:  0.6331732545253048\n"
     ]
    }
   ],
   "source": [
    "# Compute median of Dice\n",
    "median_dice = np.median(df_val['Dice'])\n",
    "print('Median Dice: ', median_dice)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram of tumor size\n",
    "plt.hist(df_val['Tumor size [mm]'], bins=50)\n",
    "plt.xlabel('Approximate tumor size from volume (treated like cube) [mm]')\n",
    "plt.ylabel('Number of subjects')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram of Dice\n",
    "plt.hist(df_val['Dice'], bins=50)\n",
    "plt.xlabel('Dice')\n",
    "plt.ylabel('Number of subjects')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Dice vs tumor volume\n",
    "plt.scatter(df_val['Tumor volume (voxels)'], df_val['Dice'])\n",
    "plt.xlabel('Tumor volume (voxels)')\n",
    "plt.ylabel('Dice')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Dice vs tumor size\n",
    "plt.scatter(df_val['Tumor size [mm]'], df_val['Dice'])\n",
    "plt.xlabel('Tumor size [mm]')\n",
    "plt.ylabel('Dice')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot average Dice score as a function of tumor size\n",
    "df_val_copy = df_val.copy()\n",
    "df_val_copy['Tumor size [mm]'] = df_val_copy['Tumor size [mm]'].round(0)\n",
    "df_val_copy = df_val_copy.groupby('Tumor size [mm]').mean()\n",
    "plt.plot(df_val_copy['Dice'])\n",
    "plt.xlabel('Tumor size [mm]')\n",
    "plt.ylabel('Average Dice')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot FP histogram\n",
    "plt.hist(df_val['FP'], bins=50)\n",
    "plt.xlabel('FP')\n",
    "plt.ylabel('Number of subjects')\n",
    "# Set x-axis range \n",
    "plt.xlim(0, 10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram of PPV\n",
    "plt.hist(df_val['PPV'], bins=50)\n",
    "plt.xlabel('PPV')\n",
    "plt.ylabel('Number of subjects')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Plot FN / volume histogram\n",
    "plt.hist(df_val['FN'] / df_val['Tumor volume (voxels)'], bins=50)\n",
    "plt.xlabel('FN / volume')\n",
    "plt.ylabel('Number of subjects')\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.10.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}