AI Medical Compendium Topic:
Radiotherapy Planning, Computer-Assisted

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Can the Student Outperform the Master? A Plan Comparison Between Pinnacle Auto-Planning and Eclipse knowledge-Based RapidPlan Following a Prostate-Bed Plan Competition.

Technology in cancer research & treatment
PURPOSE: Pinnacle Auto-Planning and Eclipse RapidPlan are 2 major commercial automated planning engines that are fundamentally different: Auto-Planning mimics real planners in the iterative optimization, while RapidPlan generates static dose objectiv...

[Impact of DVH Outliers Registered in Knowledge-based Planning on Volumetric Modulated Arc Therapy Treatment Planning for Prostate Cancer].

Nihon Hoshasen Gijutsu Gakkai zasshi
RapidPlan, a knowledge-based planning software, uses a model library containing the dose-volume histogram (DVH) of previous treatment plans, and it automatically provides optimization objectives based on a trained model to future patients for volumet...

[Prediction of three-dimensional dose distribution in intensity-modulated radiation therapy based on neural network learning].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To establish the association between the geometric anatomical characteristics of the patients and the corresponding three-dimensional (3D) dose distribution of radiotherapy plan via feed-forward back-propagation neural network for clinical...

[A Software Platform of Treatment Planning System for Radiotherapy Snake Robot].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
A software platform integrated of radiation treatment planning system and navigation system has been developed for a newly-developed snake robot. This platform is developed in a module-plugin form based on 3D Slicer medical image visualization and an...

Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.

Medical physics
PURPOSE: Accurate segmentation of organs-at-risks (OARs) is the key step for efficient planning of radiation therapy for head and neck (HaN) cancer treatment. In the work, we proposed the first deep learning-based algorithm, for segmentation of OARs ...

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery.

Medical physics
PURPOSE: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an i...

A mathematical framework for virtual IMRT QA using machine learning.

Medical physics
PURPOSE: It is common practice to perform patient-specific pretreatment verifications to the clinical delivery of IMRT. This process can be time-consuming and not altogether instructive due to the myriad sources that may produce a failing result. The...

Automated fluence map optimization based on fuzzy inference systems.

Medical physics
PURPOSE: The planning of an intensity modulated radiation therapy treatment requires the optimization of the fluence intensities. The fluence map optimization (FMO) is many times based on a nonlinear continuous programming problem, being necessary fo...

Dosimetric and delivery efficiency investigation for treating hepatic lesions with a MLC-equipped robotic radiosurgery-radiotherapy combined system.

Medical physics
PURPOSE: The CyberKnife M6 (CK-M6) Series introduced a multileaf collimator (MLC) for extending its capability from stereotactic radiosurgery/stereotactic radiotherapy (SBRT) to conventionally fractionated radiotherapy. This work is to investigate th...