The paper presents a couch-based active motion compensation strategy evaluated in simulation and validated experimentally using both a research and a clinical Elekta Precise Table™. The control strategy combines a Kalman filter to predict the surrogate motion used as a reference by a linear model predictive controller with the control action calculation based on estimated position and velocity feedback provided by an observer as well as predicted couch position and velocity using a linearized state space model. An inversion technique is used to compensate for the dead-zone nonlinearity. New generic couch models are presented and applied to model the Elekta Precise Table™ dynamics and nonlinearities including dead zone. Couch deflection was measured for different manufacturers and found to be up to 25 mm. A feed-forward approach is proposed to compensate for such couch deflection. Simultaneous motion compensation for longitudinal, lateral and vertical motions was evaluated using arbitrary trajectories generated from sensors or loaded from files. Tracking errors were between 0.5 and 2 mm RMS. A dosimetric evaluation of the motion compensation was done using a sinusoidal waveform. No notable differences were observed between films obtained for a fixed- or motion-compensated target. Further dosimetric improvement could be made by combining gating, based on tracking error together with beam on/off time, and PSS compensation.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1088/0031-9155/57/18/5787 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The Cost of Regulating Effort: Reward and Difficulty Cues With Longer Prediction Horizons Have a Stronger Impact on Performance.
J Cogn
January 2025
Department of Experimental Psychology, Ghent University, Belgium.
Many theories on cognitive effort start from the assumption that cognitive effort can be expended at will, and flexibly up- or down-regulated depending on expected task demand and rewards. However, while effort regulation has been investigated across a wide range of incentive conditions, few investigated the cost of effort regulation itself. Across four experiments, we studied the effects of reward expectancy and task difficulty on effort expenditure in a perceptual decision-making task (random-dot-motion) and a cognitive control task (colour-naming Stroop), and within each task comparted cues between short (cueing the next trial) and long (cueing the next six trials) prediction horizons.
View Article and Find Full Text PDFIdentification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram.
NPJ Digit Med
January 2025
Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to identify novel ECG features using deep learning to enhance WMA detection, referencing echocardiography as the gold standard. We collected ECG and echocardiogram data from 35,210 patients in California and labeled WMA using unstructured language parsing of echocardiographic reports.
View Article and Find Full Text PDFLameness Recognition of Dairy Cows Based on Compensation Behaviour Analysis by Swing and Posture Features from Top View Depth Image.
Animals (Basel)
December 2024
College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Top-view systems for lameness detection have advantages such as easy installation and minimal impact on farm work. However, the unclear lameness motion characteristics of the back result in lower recognition accuracy for these systems. Therefore, we analysed the compensatory behaviour of cows based on top-view walking videos, extracted compensatory motion features (CMFs), and constructed a model for recognising lameness in cows.
View Article and Find Full Text PDFThe Family Doctor in the "COVID-19 Era".
Healthcare (Basel)
December 2024
Internal Medicine I-Discipline of Medical Semiology I, Department V, Center of Advanced Research in Cardiology and Hemostasology, "Victor Babeș" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania.
The SARS-CoV-2 virus infection, the most severe pandemic in recent human history, found healthcare systems around the world more or less unprepared. Adjusting to this challenge involved changes in the daily routines of healthcare systems, as well as the patients, once again highlighting the importance of primary care (family physician or general practitioner). In the context of the COVID-19 pandemic, the family doctor in Romania played a crucial role in patient management, rapidly adapting to the changes and challenges imposed by the state of emergency.
View Article and Find Full Text PDFPurpose: With the widespread introduction of dual energy computed tomography (DECT), applications utilizing the spectral information to perform material decomposition became available. Among these, a popular application is to decompose contrast-enhanced CT images into virtual non-contrast (VNC) or virtual non-iodine images and into iodine maps. In 2021, photon-counting CT (PCCT) was introduced, which is another spectral CT modality.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!