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DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
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University of California, Los Angeles
DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
To achieve more favorable clinical VMAT/IMRT outcomes, preclinical studies that mimic clinical practices and provide highly statistically significant small animal (SA) studies are essential. However, such high-throughput studies are currently impractical beca...
Manual segmentation of immunohistochemical (IHC) stained images is a time-consuming task that typically takes 1-2 workdays to segment all images needed for analysis. Deep learning-based methods were employed to create an AI model to automatically segment IHC...
Routine and pre-treatment clinical irradiator quality assurance (QA) is vital for ensuring safe, accurate, and reproducible patient care. A primary factor limiting statistical significance in preclinical research is the lack of reproducibility, mainly due to...