To develop a method to automatically determine intrafraction motion of the prostate based on soft tissue contrast on 3D cine-magnetic resonance (MR) images with high spatial and temporal resolution. Twenty-nine patients who underwent prostate stereotactic body radiotherapy (SBRT), with four implanted cylindrical gold fiducial markers (FMs), had cine-MR imaging sessions after each of five weekly fractions. Each cine-MR session consisted of 55 sequentially obtained 3D data sets ('dynamics') and was acquired over an 11 s period, covering a total of 10 min. The prostate was delineated on the first dynamic of every dataset and this delineation was used as the starting position for the soft tissue tracking (SST). Each subsequent dynamic was rigidly aligned to the first dynamic, based on the contrast of the prostate. The obtained translation and rotation describes the intrafraction motion of the prostate. The algorithm was applied to 6270 dynamics over 114 scans of 29 patients and the results were validated by comparing to previously obtained fiducial marker tracking data of the same dataset. Our proposed tracking method was also retro-perspectively applied to cine-MR images acquired during MR-guided radiotherapy of our first prostate patient treated on the MR-Linac. The difference in the 3D translation results between the soft tissue and marker tracking was below 1 mm for 98.2% of the time. The mean translation at 10 min were X: 0.0 [Formula: see text] 0.8 mm, Y: 1.0 [Formula: see text] 1.8 mm and Z: [Formula: see text] mm. The mean rotation results at 10 min were X: [Formula: see text], Y: 0.1 [Formula: see text] 0.6° and Z: 0.0 [Formula: see text] 0.7°. A fast, robust and accurate SST algorithm was developed which obviates the need for FMs during MR-guided prostate radiotherapy. To our knowledge, this is the first data using full 3D cine-MR images for real-time soft tissue prostate tracking, which is validated against previously obtained marker tracking data.
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Sci Rep
January 2025
Faculty of Computers and Information, Minia University, Minia, Egypt.
This paper proposes a hybridized model for air quality forecasting that combines the Support Vector Regression (SVR) method with Harris Hawks Optimization (HHO) called (HHO-SVR). The proposed HHO-SVR model utilizes five datasets from the environmental protection agency's Downscaler Model (DS) to predict Particulate Matter ([Formula: see text]) levels. In order to assess the efficacy of the suggested HHO-SVR forecasting model, we employ metrics such as Mean Absolute Percentage Error (MAPE), Average, Standard Deviation (SD), Best Fit, Worst Fit, and CPU time.
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January 2025
Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, AlbaNova University Center, SE-10691, Stockholm, Sweden.
Non-trivial band topology along with magnetism leads to different novel quantum phases. When time-reversal symmetry is broken in three-dimensional topological insulators (TIs) through, e.g.
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January 2025
Changchun Automobile Economic & Technological Development Zone Employment Service Bureau, Jilin City, China.
The permanent magnet synchronous motor control system is characterized by its nonlinear and strongly coupled complexity, presenting significant challenges for control performance optimization. To address these challenges, a Fuzzy adaptive fractional order [Formula: see text] control strategy based on torque observation compensation is proposed. The parameters of the fractional order [Formula: see text] controller are optimized real time using fuzzy logic reasoning, in order to enhance the speed of parameters tuning, a graphical design method of the fractional order [Formula: see text] controller parameters based on frequency domain performance indicators is proposed to obtain the initial values of the fuzzy adaptive fractional order [Formula: see text] controller parameters graphically and intuitively.
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January 2025
TH-PPM Group, Physics Department, Faculty of Science, Beni-Suef University, Beni-Suef, 62521, Egypt.
A wealth of details regarding an individual's state of health, like a person's respiratory and metabolic functioning, can be studied by analyzing the volatile molecules and atoms in human exhaled breath. Besides, the salinity of seawater is a crucial factor in understanding its characteristics because any variation in the salinity of seawater represents the variations in the hydrological, biological, and chemical distributions. In this paper, a symmetrical one-dimensional phononic structure is theoretically designed using two symmetrical crystals separated with a defective cavity.
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January 2025
Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh, 11543, Saudi Arabia.
Underwater environmental exploration using sensor nodes has emerged as a critical endeavor fraught with challenges such as localization errors, energy, and costs attributed to the dynamic nature of underwater environments. This paper proposes a KNN-based cost-efficient machine-learning algorithm aimed at optimizing underwater context acquisition with sensor nodes. By addressing existing localization challenges, the algorithm minimizes localization errors, energy consumption and Time costs while significantly enhancing localization accuracy to 99.
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