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DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
Author profile
Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China
DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
This study proposes an automated quality assurance (QA) method for radiation therapy structure delineation based on the RT contour QA software, addressing issues such as low efficiency in delineating clinical radiation therapy regions of interest (ROIs), sign...
To explore the feasibility of applying large language models (LLMs) for radiotherapy plan(RTP) evaluation to assist radiotherapy plan quality control and clinical decision making.
To investigate the inter- and intra-fractional morphological and dosimetric variations in precision radiotherapy for bladder cancer using Fan Beam CT (FBCT) and Electronic Portal Imaging Device (EPID), providing evidence for motion management.
Based on measured failure data and adverse event records from five sentinel hospitals, this study compares failure characteristics of medical electron linear accelerators (LA) across brands, regions and service life, clarifies core failure modes, evolutionary...
To analyze the morphological and dosimetric variations in bladder patients during radiotherapy, and establish a dose-anatomy adaptive radiotherapy(ART) triggering model, providing a basis for individualized ART in clinical practice.
This study proposed the residual dynamic transformer-nnU-Net (RDT-nnU-Net) for automated delineation of esophageal cancer and adjacent organs at risk (OARs) in radiotherapy, aiming to improve accuracy, coverage, and adaptability across radiotherapy strategies.