DataExploration/DataExplorationCMMD.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Data Exploration of 22GB Chinese Breast Cancer DB\n",
    "\n",
    "James Medel\n",
    "\n",
    "The Chinese Mammography (MG) Database was collected from patients in China with benign and malignant breast disease who did mammography examinations between July 2012 and January 2016.\n",
    "\n",
    "This dataset contains the following characteristics:\n",
    "\n",
    "- 1775 Number of Patients\n",
    "- 1775 Number of Studies\n",
    "- 1775 Number of Series\n",
    "- 5202 Number of Images\n",
    "- Images Size is 22.9 GB\n",
    "\n",
    "Mammography images were collected in .TIFF format and converted to DICOM.\n",
    "\n",
    "Clinical data is in .XLSX spreadsheet. For rows where both ID1 and ID2 exist, TCIA image database stores ONLY the ID2 value as PatientID.\n",
    "\n",
    "**Data Citation**\n",
    "\n",
    "Cui, Chunyan; Li Li; Cai, Hongmin; Fan, Zhihao; Zhang, Ling; Dan, Tingting; Li, Jiao; Wang, Jinghua. (2021) The Chinese Mammography Database (CMMD): An online mammography database with biopsy confirmed types for machine diagnosis of breast. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/tcia.eqde-4b16\n",
    "\n",
    "**Publication Citation**\n",
    "\n",
    "Cai, H., Huang, Q., Rong, W., Song, Y., Li, J., Wang, J., Chen, J., & Li, L. (2019). Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms. Computational and Mathematical Methods in Medicine, 2019, 1–10. https://doi.org/10.1155/2019/2717454\n",
    "\n",
    "Wang, J., Yang, X., Cai, H., Tan, W., Jin, C., & Li, L. (2016). Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning. Scientific Reports, 6(1). https://doi.org/10.1038/srep27327\n",
    "\n",
    "**TCIA Citation**\n",
    "\n",
    "Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import pandas as pd\n",
    "import pydicom as dicom\n",
    "import matplotlib.pylab as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Breast Cancer Clinical Data Revision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID1</th>\n",
       "      <th>LeftRight</th>\n",
       "      <th>Age</th>\n",
       "      <th>number</th>\n",
       "      <th>abnormality</th>\n",
       "      <th>classification</th>\n",
       "      <th>subtype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D1-0001</td>\n",
       "      <td>R</td>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>calcification</td>\n",
       "      <td>Benign</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D1-0002</td>\n",
       "      <td>L</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>calcification</td>\n",
       "      <td>Benign</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D1-0003</td>\n",
       "      <td>L</td>\n",
       "      <td>39</td>\n",
       "      <td>2</td>\n",
       "      <td>calcification</td>\n",
       "      <td>Benign</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D1-0004</td>\n",
       "      <td>L</td>\n",
       "      <td>41</td>\n",
       "      <td>2</td>\n",
       "      <td>calcification</td>\n",
       "      <td>Benign</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D1-0005</td>\n",
       "      <td>R</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>calcification</td>\n",
       "      <td>Benign</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1857</th>\n",
       "      <td>D2-0735</td>\n",
       "      <td>L</td>\n",
       "      <td>48</td>\n",
       "      <td>2</td>\n",
       "      <td>mass</td>\n",
       "      <td>Malignant</td>\n",
       "      <td>Luminal B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858</th>\n",
       "      <td>D2-0736</td>\n",
       "      <td>R</td>\n",
       "      <td>48</td>\n",
       "      <td>2</td>\n",
       "      <td>mass</td>\n",
       "      <td>Malignant</td>\n",
       "      <td>Luminal A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859</th>\n",
       "      <td>D2-0737</td>\n",
       "      <td>R</td>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>mass</td>\n",
       "      <td>Malignant</td>\n",
       "      <td>Luminal B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1860</th>\n",
       "      <td>D2-0738</td>\n",
       "      <td>R</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>mass</td>\n",
       "      <td>Malignant</td>\n",
       "      <td>HER2-enriched</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861</th>\n",
       "      <td>D2-0739</td>\n",
       "      <td>R</td>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>mass</td>\n",
       "      <td>Malignant</td>\n",
       "      <td>Luminal B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1862 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ID1 LeftRight  Age  number    abnormality classification  \\\n",
       "0     D1-0001         R   44       2  calcification         Benign   \n",
       "1     D1-0002         L   40       2  calcification         Benign   \n",
       "2     D1-0003         L   39       2  calcification         Benign   \n",
       "3     D1-0004         L   41       2  calcification         Benign   \n",
       "4     D1-0005         R   42       2  calcification         Benign   \n",
       "...       ...       ...  ...     ...            ...            ...   \n",
       "1857  D2-0735         L   48       2           mass      Malignant   \n",
       "1858  D2-0736         R   48       2           mass      Malignant   \n",
       "1859  D2-0737         R   44       2           mass      Malignant   \n",
       "1860  D2-0738         R   43       2           mass      Malignant   \n",
       "1861  D2-0739         R   49       2           mass      Malignant   \n",
       "\n",
       "            subtype  \n",
       "0               NaN  \n",
       "1               NaN  \n",
       "2               NaN  \n",
       "3               NaN  \n",
       "4               NaN  \n",
       "...             ...  \n",
       "1857      Luminal B  \n",
       "1858      Luminal A  \n",
       "1859      Luminal B  \n",
       "1860  HER2-enriched  \n",
       "1861      Luminal B  \n",
       "\n",
       "[1862 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmmd_table = pd.read_excel(\"/home/james/Downloads/Jetson_TX2_CMPE258/Chinese_Breast_Cancer_MG_Clinical_CMMD_100Percent/CMMD_clinicaldata_revision.xlsx\")\n",
    "cmmd_table.head(-10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Breast Cancer Metadata Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Series UID</th>\n",
       "      <th>Collection</th>\n",
       "      <th>3rd Party Analysis</th>\n",
       "      <th>Data Description URI</th>\n",
       "      <th>Subject ID</th>\n",
       "      <th>Study UID</th>\n",
       "      <th>Study Description</th>\n",
       "      <th>Study Date</th>\n",
       "      <th>Series Description</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Modality</th>\n",
       "      <th>SOP Class Name</th>\n",
       "      <th>SOP Class UID</th>\n",
       "      <th>Number of Images</th>\n",
       "      <th>File Size</th>\n",
       "      <th>File Location</th>\n",
       "      <th>Download Timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.292560899611...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0003</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.113089024322...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0003/07-18-2011-NA-NA-25491/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:33.288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.610823649257...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0002</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.241519791051...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0002/07-18-2010-NA-NA-49231/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:41.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.623006463861...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0001</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.335790956129...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0001/07-18-2010-NA-NA-79377/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:42.655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.411712488433...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0005</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.249693111563...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0005/07-18-2011-NA-NA-52347/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:47.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.328825651506...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0004</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.132173027545...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0004/07-18-2011-NA-NA-14914/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:47.109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.202447815325...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0006</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.241563313733...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0006/07-18-2010-NA-NA-16802/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:49.361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.186486081393...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0009</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.336063878508...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0009/07-18-2010-NA-NA-81159/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:57.164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.148395128205...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0007</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.225080655188...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0007/07-18-2010-NA-NA-58107/1.000000...</td>\n",
       "      <td>2022-09-15T17:07:57.221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.299888293271...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0011</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.201630080467...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0011/07-18-2010-NA-NA-93954/1.000000...</td>\n",
       "      <td>2022-09-15T17:08:02.883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.642120288324...</td>\n",
       "      <td>CMMD</td>\n",
       "      <td>NO</td>\n",
       "      <td>https://doi.org/10.7937/tcia.eqde4b16</td>\n",
       "      <td>D1-0010</td>\n",
       "      <td>1.3.6.1.4.1.14519.5.2.1.1239.1759.212060565147...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07-18-2010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MG</td>\n",
       "      <td>Digital Mammography X-Ray Image Storage - For ...</td>\n",
       "      <td>1.2.840.10008.5.1.4.1.1.1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>8.79 MB</td>\n",
       "      <td>./CMMD/D1-0010/07-18-2010-NA-NA-56931/1.000000...</td>\n",
       "      <td>2022-09-15T17:08:02.891</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Series UID Collection  \\\n",
       "0  1.3.6.1.4.1.14519.5.2.1.1239.1759.292560899611...       CMMD   \n",
       "1  1.3.6.1.4.1.14519.5.2.1.1239.1759.610823649257...       CMMD   \n",
       "2  1.3.6.1.4.1.14519.5.2.1.1239.1759.623006463861...       CMMD   \n",
       "3  1.3.6.1.4.1.14519.5.2.1.1239.1759.411712488433...       CMMD   \n",
       "4  1.3.6.1.4.1.14519.5.2.1.1239.1759.328825651506...       CMMD   \n",
       "5  1.3.6.1.4.1.14519.5.2.1.1239.1759.202447815325...       CMMD   \n",
       "6  1.3.6.1.4.1.14519.5.2.1.1239.1759.186486081393...       CMMD   \n",
       "7  1.3.6.1.4.1.14519.5.2.1.1239.1759.148395128205...       CMMD   \n",
       "8  1.3.6.1.4.1.14519.5.2.1.1239.1759.299888293271...       CMMD   \n",
       "9  1.3.6.1.4.1.14519.5.2.1.1239.1759.642120288324...       CMMD   \n",
       "\n",
       "  3rd Party Analysis                   Data Description URI Subject ID  \\\n",
       "0                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0003   \n",
       "1                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0002   \n",
       "2                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0001   \n",
       "3                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0005   \n",
       "4                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0004   \n",
       "5                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0006   \n",
       "6                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0009   \n",
       "7                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0007   \n",
       "8                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0011   \n",
       "9                 NO  https://doi.org/10.7937/tcia.eqde4b16    D1-0010   \n",
       "\n",
       "                                           Study UID  Study Description  \\\n",
       "0  1.3.6.1.4.1.14519.5.2.1.1239.1759.113089024322...                NaN   \n",
       "1  1.3.6.1.4.1.14519.5.2.1.1239.1759.241519791051...                NaN   \n",
       "2  1.3.6.1.4.1.14519.5.2.1.1239.1759.335790956129...                NaN   \n",
       "3  1.3.6.1.4.1.14519.5.2.1.1239.1759.249693111563...                NaN   \n",
       "4  1.3.6.1.4.1.14519.5.2.1.1239.1759.132173027545...                NaN   \n",
       "5  1.3.6.1.4.1.14519.5.2.1.1239.1759.241563313733...                NaN   \n",
       "6  1.3.6.1.4.1.14519.5.2.1.1239.1759.336063878508...                NaN   \n",
       "7  1.3.6.1.4.1.14519.5.2.1.1239.1759.225080655188...                NaN   \n",
       "8  1.3.6.1.4.1.14519.5.2.1.1239.1759.201630080467...                NaN   \n",
       "9  1.3.6.1.4.1.14519.5.2.1.1239.1759.212060565147...                NaN   \n",
       "\n",
       "   Study Date  Series Description  Manufacturer Modality  \\\n",
       "0  07-18-2011                 NaN           NaN       MG   \n",
       "1  07-18-2010                 NaN           NaN       MG   \n",
       "2  07-18-2010                 NaN           NaN       MG   \n",
       "3  07-18-2011                 NaN           NaN       MG   \n",
       "4  07-18-2011                 NaN           NaN       MG   \n",
       "5  07-18-2010                 NaN           NaN       MG   \n",
       "6  07-18-2010                 NaN           NaN       MG   \n",
       "7  07-18-2010                 NaN           NaN       MG   \n",
       "8  07-18-2010                 NaN           NaN       MG   \n",
       "9  07-18-2010                 NaN           NaN       MG   \n",
       "\n",
       "                                      SOP Class Name  \\\n",
       "0  Digital Mammography X-Ray Image Storage - For ...   \n",
       "1  Digital Mammography X-Ray Image Storage - For ...   \n",
       "2  Digital Mammography X-Ray Image Storage - For ...   \n",
       "3  Digital Mammography X-Ray Image Storage - For ...   \n",
       "4  Digital Mammography X-Ray Image Storage - For ...   \n",
       "5  Digital Mammography X-Ray Image Storage - For ...   \n",
       "6  Digital Mammography X-Ray Image Storage - For ...   \n",
       "7  Digital Mammography X-Ray Image Storage - For ...   \n",
       "8  Digital Mammography X-Ray Image Storage - For ...   \n",
       "9  Digital Mammography X-Ray Image Storage - For ...   \n",
       "\n",
       "                 SOP Class UID  Number of Images File Size  \\\n",
       "0  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "1  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "2  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "3  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "4  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "5  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "6  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "7  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "8  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "9  1.2.840.10008.5.1.4.1.1.1.2                 2   8.79 MB   \n",
       "\n",
       "                                       File Location       Download Timestamp  \n",
       "0  ./CMMD/D1-0003/07-18-2011-NA-NA-25491/1.000000...  2022-09-15T17:07:33.288  \n",
       "1  ./CMMD/D1-0002/07-18-2010-NA-NA-49231/1.000000...   2022-09-15T17:07:41.45  \n",
       "2  ./CMMD/D1-0001/07-18-2010-NA-NA-79377/1.000000...  2022-09-15T17:07:42.655  \n",
       "3  ./CMMD/D1-0005/07-18-2011-NA-NA-52347/1.000000...  2022-09-15T17:07:47.106  \n",
       "4  ./CMMD/D1-0004/07-18-2011-NA-NA-14914/1.000000...  2022-09-15T17:07:47.109  \n",
       "5  ./CMMD/D1-0006/07-18-2010-NA-NA-16802/1.000000...  2022-09-15T17:07:49.361  \n",
       "6  ./CMMD/D1-0009/07-18-2010-NA-NA-81159/1.000000...  2022-09-15T17:07:57.164  \n",
       "7  ./CMMD/D1-0007/07-18-2010-NA-NA-58107/1.000000...  2022-09-15T17:07:57.221  \n",
       "8  ./CMMD/D1-0011/07-18-2010-NA-NA-93954/1.000000...  2022-09-15T17:08:02.883  \n",
       "9  ./CMMD/D1-0010/07-18-2010-NA-NA-56931/1.000000...  2022-09-15T17:08:02.891  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmmd_meta_table = pd.read_csv(\"/home/james/Downloads/Jetson_TX2_CMPE258/Chinese_Breast_Cancer_MG_Clinical_CMMD_100Percent/manifest-1616439774456/metadata.csv\")\n",
    "cmmd_meta_table.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load MG BreastD1-0001\n",
    "\n",
    "Let's preview MG dicom  **1-1.dcm** without extracting any info:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f7793d64430>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image_path = \"/home/james/Downloads/Jetson_TX2_CMPE258/Chinese_Breast_Cancer_MG_Clinical_CMMD_100Percent/manifest-1616439774456/CMMD/D1-0001/07-18-2010-NA-NA-79377/1.000000-NA-70244/1-1.dcm\"\n",
    "ds = dicom.dcmread(image_path)\n",
    "\n",
    "plt.imshow(ds.pixel_array, cmap=plt.cm.gray)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load MG BreastD1-0051"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f77967f3490>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image_path = \"/home/james/Downloads/Jetson_TX2_CMPE258/Chinese_Breast_Cancer_MG_Clinical_CMMD_100Percent/manifest-1616439774456/CMMD/D1-0051/07-18-2010-NA-NA-81300/1.000000-NA-84975/1-1.dcm\"\n",
    "ds = dicom.dcmread(image_path)\n",
    "\n",
    "plt.imshow(ds.pixel_array, cmap=plt.cm.gray)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load MG BreastD1-0101"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f77967d13a0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image_path = \"/home/james/Downloads/Jetson_TX2_CMPE258/Chinese_Breast_Cancer_MG_Clinical_CMMD_100Percent/manifest-1616439774456/CMMD/D1-0101/07-18-2010-NA-NA-36396/1.000000-NA-00552/1-1.dcm\"\n",
    "ds = dicom.dcmread(image_path)\n",
    "\n",
    "plt.imshow(ds.pixel_array, cmap=plt.cm.gray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.13 ('cmpe258_dev')",
   "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": "3.8.15"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "8825c41d7d1c6f051ca509d046896e55ebe94d05a46bc86a80aa5ae56692da7a"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}