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DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
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Department of Radiation Oncology, NYU Langone Health
DICOMAnon helps imaging teams anonymize, batch process, and automate DICOM workflows without writing custom scripts.
To evaluate the accuracy of the Enhanced Leaf Model (ELM) implemented in Eclipse v18.0 for single-isocenter multiple-target (SIMT) stereotactic radiosurgery (SRS), with emphasis on updated MLC modeling and dosimetric precision.
This work introduces a framework to automate treatment planning of small-volume lattice radiotherapy applied to head and neck malignancies.
Understanding of medical physics is essential for safe and effective radiation oncology practice. This study evaluates current instructional practices for physics education in radiation oncology physician residency programs following the release of the AAPM/A...
To evaluate the feasibility of HyperSight CBCT–based radiotherapy planning on the Varian Ethos v2.0 platform and to develop a clinically deployable simulation workflow that overcomes current system limitations.
VMAT based cerebrospinal irradiation (CSI) using photons has emerged as a palliative treatment approach for patients suffering from metastatic leptomeningeal disease. In this work we describe the experience introducing VMAT CSI into clinical use.
This study characterized inter-machine variations in physical leaf gaps and associated MLC parameters, including dosimetric leaf gap (DLG) and leaf gap (LG). We provide practical guidance for robust Enhanced Leaf Model (ELM) implementation through physical le...
Oncology information system (OIS) and Treatment planning system (TPS) upgrades are high-impact events that require comprehensive validation. Knowing what to prepare, who to involve, and what to test on go-live day is critical for patient safety and clinical c...