A Method of Rapid Quantification of Patient-Specific Organ Doses for CT Using Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing.

08:00 EDT 10th March 2020 | BioPortfolio

Summary of "A Method of Rapid Quantification of Patient-Specific Organ Doses for CT Using Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing."

One technical barrier to patient-specific CT dosimetry has been the lack of computational tools for the automatic patient-specific multi-organ segmentation of CT images and rapid organ dose quantification. When previous CT images are available for the same body region of the patient, the ability to obtain patient-specific organ doses for CT - in a similar manner as radiation therapy treatment planning - will open the door to personalized and prospective CT scan protocols. This study aims to demonstrate the feasibility of combining deep-learning algorithms for automatic segmentation of multiple radiosensitive organs from CT images with the GPU-based Monte Carlo rapid organ dose calculation.


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Name: Medical physics
ISSN: 2473-4209


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