AIMC Topic: Radiotherapy Dosage

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Managing tumor changes during radiotherapy using a deep learning model.

Medical physics
PURPOSE: We propose a treatment planning framework that accounts for weekly lung tumor shrinkage using cone beam computed tomography (CBCT) images with a deep learning-based model.

Personalized brachytherapy dose reconstruction using deep learning.

Computers in biology and medicine
BACKGROUND AND PURPOSE: Accurate calculation of the absorbed dose delivered to the tumor and normal tissues improves treatment gain factor, which is the major advantage of brachytherapy over external radiation therapy. To address the simplifications ...

Applications of machine and deep learning to patient-specific IMRT/VMAT quality assurance.

Journal of applied clinical medical physics
In order to deliver accurate and safe treatment to cancer patients in radiation therapy using advanced techniques such as intensity modulated radiation therapy (IMRT) and volumetric-arc radiation therapy (VMAT), patient specific quality assurance (QA...

Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT.

Radiation oncology (London, England)
BACKGROUND: This study aimed to (1) develop a fully residual deep convolutional neural network (CNN)-based segmentation software for computed tomography image segmentation of the male pelvic region and (2) demonstrate its efficiency in the male pelvi...

A feasibility study on deep learning-based individualized 3D dose distribution prediction.

Medical physics
PURPOSE: Radiation therapy treatment planning is a trial-and-error, often time-consuming process. An approximately optimal dose distribution corresponding to a specific patient's anatomy can be predicted by using pre-trained deep learning (DL) models...

DeepBeam: a machine learning framework for tuning the primary electron beam of the PRIMO Monte Carlo software.

Radiation oncology (London, England)
BACKGROUND: Any Monte Carlo simulation of dose delivery using medical accelerator-generated megavolt photon beams begins by simulating electrons of the primary electron beam interacting with a target. Because the electron beam characteristics of any ...

Interobserver variability in organ at risk delineation in head and neck cancer.

Radiation oncology (London, England)
BACKGROUND: In radiotherapy inaccuracy in organ at risk (OAR) delineation can impact treatment plan optimisation and treatment plan evaluation. Brouwer et al. showed significant interobserver variability (IOV) in OAR delineation in head and neck canc...

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topi...