Investigators at the Mayo Clinic, with funding from the National Institute of Biomedical Imaging and Bioengineering (EB 017185), have built a library of CT patient projection data in an open and vendor-neutral format. This format, referred to as DICOM-CT-PD (1), is an extended DICOM format that contains CT projection data and acquisition geometry. The de-identified patient projection data in the library were decoded with help of the manufacturer and have been converted into an open standardized format. Reconstructed images, patient age and gender, and pathology annotation are also provided in these de-identified data sets. The library consists of scans from various exam types, including non-contrast head CT scans acquired for acute cognitive or motor deficit, low-dose non-contrast chest scans acquired to screen high-risk patients for pulmonary nodules, and contrast-enhanced CT scans of the abdomen acquired to look for metastatic liver lesions. For each scan, three types of data are provided, including DICOM-CT-PD projection data, reconstructed CT images, and a CSV file. CT data are provided for both full and simulated lower dose levels, albeit reconstructed image data of the lower dose projection data are available only for the data from Siemens Healthcare, where we were able to return the lower dose data to the scanner for reconstruction with their commercial filtered-back-projection algorithm. Several instructional documents are provided to help users extract needed information from the DICOM-CT-PD files, including a dictionary file for the DICOM-CT-PD format, a DICOM-CT-PD reader, and a user manual. This collection will comprise 150 head scans, 150 chest scans, and 150 abdomen scans. For each scan type, the 50 currently available cases are from a SOMATOM Definition Flash CT scanner (Siemens Healthcare, Forchheim, Germany). An additional 50 cases for each exam type are being prepared from a Lightspeed VCT CT scanner (GE Healthcare, Waukesha, WI) and 50 a Brilliance iCT CT scanner, also known as an iCT Elite, (Philips Healthcare, Best, Netherlands). Together, these data will greatly facilitate the development and validation of new CT reconstruction and/or denoising algorithms, including those associated with machine learning or artificial intelligence. Acquisition protocolAll CT scans were acquired at routine dose levels for the practice at which they were obtained using standard-clinical protocols for the anatomical region of interest. Each clinical case was processed to include a second projection dataset at a simulated lower dose level. Head and abdomen cases are provided at 25% of the routine dose and chest cases are provided at 10% of the routine dose.
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