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<h6 id="path-to-notebook-httpswwwgithubcomdata-privacy-stackpresidioblobmaindocssamplespythonexample_dicom_image_redactoripynb">Path to notebook: <a href="https://www.github.com/data-privacy-stack/presidio/blob/main/docs/samples/python/example_dicom_image_redactor.ipynb">https://www.github.com/data-privacy-stack/presidio/blob/main/docs/samples/python/example_dicom_image_redactor.ipynb</a></h6>
<h1 id="de-identifying-sensitive-burnt-in-text-in-dicom-images">De-identifying sensitive burnt-in text in DICOM images</h1>
<p>This notebook covers how to:
1. Redact text Personal Health Information (PHI) present as pixels in DICOM images
2. Visually compare original DICOM images with their redacted versions</p>
<blockquote>
<p><em>This module only redacts pixel data and does not scrub text PHI which may exist in the DICOM metadata. To redact sensitive information from metadata, consider using another package such as the <a href="https://github.com/microsoft/Tools-for-Health-Data-Anonymization">Tools for Health Data Anonymization</a>.</em></p>
</blockquote>
<h2 id="prerequisites">Prerequisites</h2>
<p>Before getting started, make sure presidio and the latest version of Tesseract OCR are installed. For detailed documentation, see the <a href="https://data-privacy-stack.github.io/presidio/installation">installation docs</a>.</p>
<div class="highlight"><pre><span></span><code><span class="err">!</span><span class="n">pip</span> <span class="n">install</span> <span class="n">presidio_analyzer</span> <span class="n">presidio_anonymizer</span> <span class="n">presidio_image_redactor</span>
<span class="err">!</span><span class="n">python</span> <span class="o">-</span><span class="n">m</span> <span class="n">spacy</span> <span class="n">download</span> <span class="n">en_core_web_lg</span>
</code></pre></div>
<h2 id="dataset">Dataset</h2>
<p>Sample DICOM files are available for use in this notebook in <code>./sample_data</code>. Copies of the original DICOM data were saved into the folder with permission from the dataset owners. Please see the original dataset information below:</p>
<blockquote>
<p>Rutherford, M., Mun, S.K., Levine, B., Bennett, W.C., Smith, K., Farmer, P., Jarosz, J., Wagner, U., Farahani, K., Prior, F. (2021). A DICOM dataset for evaluation of medical image de-identification (Pseudo-PHI-DICOM-Data) [Data set]. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/s17z-r072</p>
</blockquote>
<div class="highlight"><pre><span></span><code><span class="kn">import</span><span class="w"> </span><span class="nn">glob</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pathlib</span><span class="w"> </span><span class="kn">import</span> <span class="n">Path</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">pydicom</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">presidio_image_redactor</span><span class="w"> </span><span class="kn">import</span> <span class="n">DicomImageRedactorEngine</span>
</code></pre></div>
<h2 id="1-setup">1. Setup</h2>
<div class="highlight"><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">compare_dicom_images</span><span class="p">(</span>
<span class="n">instance_original</span><span class="p">:</span> <span class="n">pydicom</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">FileDataset</span><span class="p">,</span>
<span class="n">instance_redacted</span><span class="p">:</span> <span class="n">pydicom</span><span class="o">.</span><span class="n">dataset</span><span class="o">.</span><span class="n">FileDataset</span><span class="p">,</span>
<span class="n">figsize</span><span class="p">:</span> <span class="nb">tuple</span> <span class="o">=</span> <span class="p">(</span><span class="mi">11</span><span class="p">,</span> <span class="mi">11</span><span class="p">)</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;Display the DICOM pixel arrays of both original and redacted as images.</span>
<span class="sd"> Args:</span>
<span class="sd"> instance_original (pydicom.dataset.FileDataset): A single DICOM instance (with text PHI).</span>
<span class="sd"> instance_redacted (pydicom.dataset.FileDataset): A single DICOM instance (redacted PHI).</span>
<span class="sd"> figsize (tuple): Figure size in inches (width, height).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">_</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">figsize</span><span class="p">)</span>
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">instance_original</span><span class="o">.</span><span class="n">pixel_array</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Original&#39;</span><span class="p">)</span>
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">instance_redacted</span><span class="o">.</span><span class="n">pixel_array</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Redacted&#39;</span><span class="p">)</span>
</code></pre></div>
<p>Instantiate the DICOM image redactor engine object.</p>
<blockquote>
<p><em>Note: The <code>DicomImageRedactorEngine</code> object can initialized with a custom <code>ImageAnalyzerEngine</code>, which may be useful in cases where DICOM metadata is insufficient.</em></p>
</blockquote>
<div class="highlight"><pre><span></span><code><span class="n">engine</span> <span class="o">=</span> <span class="n">DicomImageRedactorEngine</span><span class="p">()</span>
</code></pre></div>
<h2 id="2-redacting-from-loaded-dicom-image-data">2. Redacting from loaded DICOM image data</h2>
<p>In cases where you already working with loaded DICOM data, the <code>.redact()</code> function is most appropriate.</p>
<div class="highlight"><pre><span></span><code><span class="c1"># Load in and process your DICOM file as needed</span>
<span class="n">dicom_instance</span> <span class="o">=</span> <span class="n">pydicom</span><span class="o">.</span><span class="n">dcmread</span><span class="p">(</span><span class="s1">&#39;sample_data/0_ORIGINAL.dcm&#39;</span><span class="p">)</span>
</code></pre></div>
<div class="highlight"><pre><span></span><code><span class="c1"># Redact</span>
<span class="n">redacted_dicom_instance</span> <span class="o">=</span> <span class="n">engine</span><span class="o">.</span><span class="n">redact</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="s2">&quot;contrast&quot;</span><span class="p">)</span>
</code></pre></div>
<h3 id="22-verify-performance">2.2 Verify performance</h3>
<p>Let's look at the original input and compare against the de-identified output.</p>
<div class="highlight"><pre><span></span><code><span class="n">compare_dicom_images</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">redacted_dicom_instance</span><span class="p">)</span>
</code></pre></div>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_15_0.png" /></p>
<p>We can also set the "fill" to match the background color to blend in more with the image.</p>
<div class="highlight"><pre><span></span><code><span class="n">redacted_dicom_instance_2</span> <span class="o">=</span> <span class="n">engine</span><span class="o">.</span><span class="n">redact</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="s2">&quot;background&quot;</span><span class="p">)</span>
<span class="n">compare_dicom_images</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">redacted_dicom_instance_2</span><span class="p">)</span>
</code></pre></div>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_17_0.png" /></p>
<h3 id="23-adjust-parameters">2.3 Adjust parameters</h3>
<p>With the <code>use_metadata</code> parameter, we can toggle whether the DICOM metadata is used to augment the analyzer which determines which text to redact.</p>
<div class="highlight"><pre><span></span><code><span class="n">redacted_dicom_instance</span> <span class="o">=</span> <span class="n">engine</span><span class="o">.</span><span class="n">redact</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">use_metadata</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="c1"># default is use_metadata=True</span>
<span class="n">compare_dicom_images</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">redacted_dicom_instance</span><span class="p">)</span>
</code></pre></div>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_19_0.png" /></p>
<p>We can also return the bounding box information for the pixel regions that were redacted.</p>
<div class="highlight"><pre><span></span><code><span class="n">redacted_dicom_instance</span><span class="p">,</span> <span class="n">bbox</span> <span class="o">=</span> <span class="n">engine</span><span class="o">.</span><span class="n">redact_and_return_bbox</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">)</span>
<span class="n">compare_dicom_images</span><span class="p">(</span><span class="n">dicom_instance</span><span class="p">,</span> <span class="n">redacted_dicom_instance</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of redacted regions: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">bbox</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">bbox</span><span class="p">)</span>
</code></pre></div>
<div class="highlight"><pre><span></span><code>Number of redacted regions: 4
[{&#39;top&#39;: 0, &#39;left&#39;: 0, &#39;width&#39;: 241, &#39;height&#39;: 37}, {&#39;top&#39;: 0, &#39;left&#39;: 262, &#39;width&#39;: 230, &#39;height&#39;: 36}, {&#39;top&#39;: 1, &#39;left&#39;: 588, &#39;width&#39;: 226, &#39;height&#39;: 35}, {&#39;top&#39;: 47, &#39;left&#39;: 145, &#39;width&#39;: 218, &#39;height&#39;: 35}]
</code></pre></div>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_21_1.png" /></p>
<h2 id="3-redacting-from-dicom-files">3. Redacting from DICOM files</h2>
<p>Before instantiating your <code>DicomImageRedactorEngine</code> class, determine where you want your input to come from and where you want your output to be written to.</p>
<blockquote>
<p><strong>Note</strong>: The output will mimic the folder structure of the input if the input is a directory. The redact method will operate on all DICOM (.dcm) files in the input directory and all its subdirectories.</p>
</blockquote>
<p>To protect against overwriting the original DICOM files, the <code>redact_from_file()</code> and <code>redact_from_directory()</code> methods will not run if the <code>output_dir</code> is a directory which already contains any content.</p>
<div class="highlight"><pre><span></span><code><span class="c1"># Single DICOM (.dcm) file or directory containing DICOM files</span>
<span class="n">input_path</span> <span class="o">=</span> <span class="s1">&#39;sample_data/&#39;</span>
<span class="c1"># Directory where the output will be written</span>
<span class="n">output_parent_dir</span> <span class="o">=</span> <span class="s1">&#39;output/&#39;</span>
</code></pre></div>
<h3 id="31-run-de-identification">3.1. Run de-identification</h3>
<p>Use the <code>DicomImageRedactorEngine</code> class to process your DICOM images. If you have only one image to process and want to specify that directly instead of a directory, use <code>.redact_from_file()</code> instead of <code>.redact_from_directory()</code>.</p>
<div class="highlight"><pre><span></span><code><span class="c1"># Redact text PHI from DICOM images</span>
<span class="n">engine</span><span class="o">.</span><span class="n">redact_from_directory</span><span class="p">(</span>
<span class="n">input_dicom_path</span> <span class="o">=</span> <span class="n">input_path</span><span class="p">,</span>
<span class="n">output_dir</span> <span class="o">=</span> <span class="n">output_parent_dir</span><span class="p">,</span>
<span class="n">fill</span><span class="o">=</span><span class="s2">&quot;contrast&quot;</span><span class="p">,</span>
<span class="n">save_bboxes</span><span class="o">=</span><span class="kc">True</span> <span class="c1"># if True, saves the redacted region bounding box info to .json files in the output dir</span>
<span class="p">)</span>
</code></pre></div>
<div class="highlight"><pre><span></span><code>Output written to output\sample_data
</code></pre></div>
<h3 id="32-verify-performance">3.2. Verify performance</h3>
<p>Let's look at the original input and compare against the de-identified output.</p>
<p>Get file paths</p>
<div class="highlight"><pre><span></span><code><span class="c1"># Original DICOM images</span>
<span class="n">p</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">input_path</span><span class="p">)</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;**/*.dcm&quot;</span><span class="p">)</span>
<span class="n">original_files</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">p</span> <span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="n">is_file</span><span class="p">()]</span>
<span class="c1"># Redacted DICOM images</span>
<span class="n">p</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">output_parent_dir</span><span class="p">)</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;**/*.dcm&quot;</span><span class="p">)</span>
<span class="n">redacted_files</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">p</span> <span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="n">is_file</span><span class="p">()]</span>
</code></pre></div>
<p>Preview images</p>
<div class="highlight"><pre><span></span><code><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">original_files</span><span class="p">)):</span>
<span class="n">original_file</span> <span class="o">=</span> <span class="n">pydicom</span><span class="o">.</span><span class="n">dcmread</span><span class="p">(</span><span class="n">original_files</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="n">redacted_file</span> <span class="o">=</span> <span class="n">pydicom</span><span class="o">.</span><span class="n">dcmread</span><span class="p">(</span><span class="n">redacted_files</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="n">compare_dicom_images</span><span class="p">(</span><span class="n">original_file</span><span class="p">,</span> <span class="n">redacted_file</span><span class="p">)</span>
</code></pre></div>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_30_0.png" /></p>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_30_1.png" /></p>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_30_2.png" /></p>
<p><img alt="png" src="../example_dicom_image_redactor_files/example_dicom_image_redactor_30_3.png" /></p>
<h2 id="conclusion">Conclusion</h2>
<p>As seen in the DICOM image previews above, we see that our <code>DicomImageRedactorEngine</code> is able to successfully mask out text PHI present in the DICOM images without compromising image quality.</p>
<p><strong>Note</strong>: Performance is best when the burnt-in text is also present within the DICOM metadata. We recommend not scrubbing metadata until after performing image de-identification.</p>
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