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<h1>About Dataset</h1> |
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<h2>Abstract</h2> |
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<p> |
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This dataset comprises FDG-PET/CT and radiotherapy planning CT imaging data of <strong>298 patients</strong> from four institutions in Québec, diagnosed with histologically proven head-and-neck cancer (H&N). The dataset includes pre-treatment FDG-PET/CT scans conducted between April 2006 and November 2014. A median interval of <strong>18 days</strong> (range: 6–66 days) was maintained before treatment. For de-identification, dates in the TCIA images were altered while preserving the time intervals between serial scans. |
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</p> |
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<h2>Data Description</h2> |
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<p> |
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This subset focuses exclusively on the <strong>CT scans</strong> from the original dataset. It provides valuable insights for researchers studying head-and-neck cancer, offering a comprehensive collection of imaging data crucial for understanding tumour characteristics and treatment outcomes. |
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</p> |
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<h2>Overview of Processing Workflow</h2> |
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<p>This processing workflow is designed to handle CT scan images in DICOM format. It consists of two major phases:</p> |
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<h3>Phase 1: Normalization and Conversion (DICOM to PNG)</h3> |
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<ul> |
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<li><strong>Global Min-Max Calculation:</strong> Calculates the global minimum and maximum pixel values across all DICOM files for standardized normalization.</li> |
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</ul> |
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<h4>DICOM Image Processing:</h4> |
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<ul> |
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<li>Each DICOM file is normalized using the global min-max values.</li> |
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<li><strong>CLAHE</strong> (Contrast Limited Adaptive Histogram Equalization) is applied to enhance contrast.</li> |
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<li><strong>Histogram stretching</strong> is used for further contrast enhancement.</li> |
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</ul> |
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<h4>Conversion to PNG:</h4> |
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<ul> |
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<li>Processed images are converted into <strong>PNG format</strong> for easier handling.</li> |
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<li>Each image is uniquely named based on its slice index.</li> |
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</ul> |
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<h3>Phase 2: Upscaling and Additional Image Processing (PNG Images)</h3> |
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<h4>Image Upscaling:</h4> |
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<ul> |
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<li>Each PNG is upscaled to a higher resolution (e.g., <strong>2048×2048 pixels</strong>) using <strong>Lanczos resampling</strong>.</li> |
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</ul> |
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<h4>Additional Image Processing:</h4> |
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<ul> |
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<li><strong>Gaussian blur</strong> is applied to reduce noise and artifacts.</li> |
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<li><strong>Antialiasing</strong> is performed to improve visual clarity.</li> |
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</ul> |
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<h2>Publication Citation</h2> |
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<p> |
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Vallières, M. et al. <em>Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer.</em> Sci Rep 7, 10117 (2017). DOI: <a href="https://doi.org/10.1038/s41598-017-10371-5" target="_blank">10.1038/s41598-017-10371-5</a> |
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</p> |
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<h2>License</h2> |
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<p>Creative Commons Attribution 3.0 Unported License</p> |
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<h2>More Info</h2> |
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<p>Dataset URL: <a href="https://wiki.cancerimagingarchive.net/display/Public/Head-Neck-PET-CT" target="_blank">https://wiki.cancerimagingarchive.net/display/Public/Head-Neck-PET-CT</a></p> |