CT images with expert manual contours of thoracic cancer for benchmarking auto‐segmentation accuracy
Autor: | Jinzhong Yang, Greg Sharp, Andre Dekker, Wouter van Elmpt, Harini Veeraraghavan, Mark Gooding |
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Přispěvatelé: | Radiotherapie, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, RS: FSE BISS |
Rok vydání: | 2020 |
Předmět: |
medicine.medical_specialty
medicine.medical_treatment Thoracic cancer radiation therapy Article 030218 nuclear medicine & medical imaging automatic segmentation 03 medical and health sciences DICOM 0302 clinical medicine thoracic cancer RADIATION-THERAPY Humans Medicine Segmentation Four-Dimensional Computed Tomography Esophagus Contouring business.industry Radiotherapy Planning Computer-Assisted Cancer ASSOCIATION General Medicine Benchmarking Thoracic Neoplasms Thorax ATLAS medicine.disease Radiation therapy grand challenge medicine.anatomical_structure 030220 oncology & carcinogenesis ESOPHAGUS Radiology business LUNG CT RADIOTHERAPY |
Zdroj: | Medical Physics, 47(7), 3250-3255. Wiley Med Phys |
ISSN: | 2473-4209 0094-2405 |
Popis: | PURPOSE Automatic segmentation offers many benefits for radiotherapy treatment planning; however, the lack of publicly available benchmark datasets limits the clinical use of automatic segmentation. In this work, we present a well-curated computed tomography (CT) dataset of high-quality manually drawn contours from patients with thoracic cancer that can be used to evaluate the accuracy of thoracic normal tissue auto-segmentation systems. ACQUISITION AND VALIDATION METHODS Computed tomography scans of 60 patients undergoing treatment simulation for thoracic radiotherapy were acquired from three institutions: MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, and the MAASTRO clinic. Each institution provided CT scans from 20 patients, including mean intensity projection four-dimensional CT (4D CT), exhale phase (4D CT), or free-breathing CT scans depending on their clinical practice. All CT scans covered the entire thoracic region with a 50-cm field of view and slice spacing of 1, 2.5, or 3 mm. Manual contours of left/right lungs, esophagus, heart, and spinal cord were retrieved from the clinical treatment plans. These contours were checked for quality and edited if necessary to ensure adherence to RTOG 1106 contouring guidelines. DATA FORMAT AND USAGE NOTES The CT images and RTSTRUCT files are available in DICOM format. The regions of interest were named according to the nomenclature recommended by American Association of Physicists in Medicine Task Group 263 as Lung_L, Lung_R, Esophagus, Heart, and SpinalCord. This dataset is available on The Cancer Imaging Archive (funded by the National Cancer Institute) under Lung CT Segmentation Challenge 2017 (http://doi.org/10.7937/K9/TCIA.2017.3r3fvz08). POTENTIAL APPLICATIONS This dataset provides CT scans with well-delineated manually drawn contours from patients with thoracic cancer that can be used to evaluate auto-segmentation systems. Additional anatomies could be supplied in the future to enhance the existing library of contours. |
Databáze: | OpenAIRE |
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