AIMC Topic: Radiometry

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Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry.

Medical physics Dec 19, 2023
BACKGROUND: Dose distributions calculated with electronic portal imaging device (EPID)-based in vivo dosimetry (EIVD) differ from planned dose distributions due to generic and plan-specific deviations. Generic deviations are characteristic to a class...
Humans Male In Vivo Dosimetry Radiotherapy Dosage Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Radiometry
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Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.

International journal of radiation oncology, biology, physics Dec 5, 2023
PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the nominal biologically effective dose (BED) of 100 Gy is felt by some to be insufficient for long-term ...
Middle Aged Aged, 80 and over Deep Learning Radiosurgery Female Radiotherapy Planning, Computer-Assisted Treatment Failure Humans Male Carcinoma, Non-Small-Cell Lung Lung Neoplasms Aged Radiotherapy Dosage Radiometry Tomography, X-Ray Computed
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On the Use of Artificial Intelligence for Dosimetry of Radiopharmaceutical Therapies.

Nuklearmedizin. Nuclear medicine Oct 12, 2023
Routine clinical dosimetry along with radiopharmaceutical therapies is key for future treatment personalization. However, dosimetry is considered complex and time-consuming with various challenges amongst the required steps within the dosimetry workf...
Humans Radiometry Neoplasms Radiopharmaceuticals Artificial Intelligence
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Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

Journal of applied clinical medical physics Aug 26, 2023
PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect and classify errors of multi-leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor...
Radiotherapy, Intensity-Modulated Radiometry Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Male Deep Learning Humans
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A framework for prediction of personalized pediatric nuclear medical dosimetry based on machine learning and Monte Carlo techniques.

Physics in medicine and biology Apr 7, 2023
A methodology is introduced for the development of an internal dosimetry prediction toolkit for nuclear medical pediatric applications. The proposed study exploits Artificial Intelligence techniques using Monte Carlo simulations as ground truth for a...
Phantoms, Imaging Radiometry Radiopharmaceuticals Child, Preschool Monte Carlo Method Artificial Intelligence Child Tissue Distribution Machine Learning Male Humans Female Adolescent
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Rapid estimation of patient-specific organ doses using a deep learning network.

Medical physics Mar 23, 2023
BACKGROUND: Patient-specific organ-dose estimation in diagnostic CT examinations can provide useful insights on individualized secondary cancer risks, protocol optimization, and patient management. Current dose estimation techniques mainly rely on ti...
Humans Tomography, X-Ray Computed Monte Carlo Method Deep Learning Phantoms, Imaging Radiation Dosage Radiometry
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Geometric and dosimetric evaluation of deep learning based auto-segmentation for clinical target volume on breast cancer.

Journal of applied clinical medical physics Mar 15, 2023
BACKGROUND: Recently, target auto-segmentation techniques based on deep learning (DL) have shown promising results. However, inaccurate target delineation will directly affect the treatment planning dose distribution and the effect of subsequent radi...
Organs at Risk Radiotherapy Planning, Computer-Assisted Radiometry Breast Neoplasms Deep Learning Mastectomy Humans Female
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Dicentric chromosome assay using a deep learning-based automated system.

Scientific reports Dec 21, 2022
The dicentric chromosome assay is the "gold standard" in biodosimetry for estimating radiation exposure. However, its large-scale deployment is limited owing to its time-consuming nature and requirement for expert reviewers. Therefore, a recently dev...
Dose-Response Relationship, Radiation Radiometry Gamma Rays Deep Learning Chromosome Aberrations Chromosomes, Human Humans
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Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

Physics in medicine and biology Dec 6, 2022
Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d...
Machine Learning Radiotherapy Radiometry Neural Networks, Computer
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X-ray dose profiles using artificial neural networks.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine Nov 28, 2022
This paper introduces a novel computational method to simulate and predict radiation dose profiles in a water phantom irradiated by X-rays of 6 and 15 MV at different depths and field sizes using Artificial Neural Networks within the error margin req...
Monte Carlo Method Radiometry Humans Radiotherapy Planning, Computer-Assisted Radiography X-Rays Phantoms, Imaging Neural Networks, Computer Radiotherapy Dosage
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