AIMC Topic: Radiometry
Clear Filters Showing 1 to 10 of 119 articles
Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 1, 2025
Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared with conventional multiple-time-point image-based dosimetry. Despite numerous advancements, current ST...
Evaluating the dosimetric and positioning accuracy of a deep learning based synthetic-CT model for liver radiotherapy treatment planning.
Biomedical physics & engineering express
Apr 11, 2025
An MRI-only workflow requires synthetic computed tomography (sCT) images to enable dose calculation. This study evaluated the dosimetric and patient positioning accuracy of deep learning-generated sCT for liver radiotherapy.sCT images were generated ...
Rapid dose prediction for lung CyberKnife radiotherapy plans utilizing a deep learning approach by incorporating dosimetric features delivered by noncoplanar beams.
Biomedical physics & engineering express
Apr 8, 2025
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.
Medical physics
Apr 1, 2025
BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown rapidly, thus making available a large volume of organ dose information. With modern c...
Proton dose calculation with transformer: Transforming spot map to dose.
Medical physics
Mar 29, 2025
BACKGROUND: Conventional proton dose calculation methods are either time- and resource-intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade-off between computational efficiency and accu...
Deep learning-based segmentation of head and neck organs at risk on CBCT images with dosimetric assessment for radiotherapy.
Physics in medicine and biology
Mar 26, 2025
Cone beam computed tomography (CBCT) has become an essential tool in head and neck cancer (HNC) radiotherapy (RT) treatment delivery. Automatic segmentation of the organs at risk (OARs) on CBCT can trigger and accelerate treatment replanning but is s...
Initial characterization of a novel dual-robot orthovoltage radiotherapy system.
Biomedical physics & engineering express
Mar 17, 2025
Adequate access to radiotherapy is a critical global concern affecting low-resource settings such as low- and middle-income countries and rural regions. We propose to reduce this disparity by developing a novel low-cost radiotherapy device that treat...
Power absorption and temperature rise in deep learning based head models for local radiofrequency exposures.
Physics in medicine and biology
Mar 11, 2025
Computational uncertainty and variability of power absorption and temperature rise in humans for radiofrequency (RF) exposure is a critical factor in ensuring human protection. This aspect has been emphasized as a priority. However, accurately modeli...
Introduction of a hybrid approach based on statistical shape model and Adaptive Neural Fuzzy Inference System (ANFIS) to assess dosimetry uncertainty: A Monte Carlo study.
Computers in biology and medicine
Mar 10, 2025
The increasing use of ionizing radiation has raised concerns about adverse and long-term health risks for individuals. Therefore, to evaluate the range of risks and protection against ionizing radiation, it is necessary to assess the dosimetry calcul...
Geometric and Dosimetric Evaluation of a RayStation Deep Learning Model for Auto-Segmentation of Organs at Risk in a Real-World Head and Neck Cancer Dataset.
Clinical oncology (Royal College of Radiologists (Great Britain))
Mar 1, 2025
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823