Single-molecule force spectroscopy using optical tweezers continues to provide detailed insights into the behavior of nanoscale systems. Obtaining precise measurements of their mechanical properties is highly dependent on accurate instrument calibration. Therefore, instrumental drift or inaccurate calibration may prevent reaching an accuracy at the theoretical limit and may lead to incorrect conclusions. Commonly encountered sources of error include inaccuracies in the detector sensitivity and trap stiffness and neglecting the non-harmonicity of an optical trap at higher forces. Here, we first quantify the impact of these artifacts on force-extension data and find that a small deviation of the calibration parameters can already have a significant downstream effect. We then develop a method to identify and remove said artifacts based on differences in the theoretical and measured noise of bead fluctuations. By applying our procedure to both simulated and experimental data, we can show how effects due to miscalibration and trap non-linearities can be successfully removed. Most importantly, this correction can be performed post-measurement and could be adapted for data acquired using any force spectroscopy technique.
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http://dx.doi.org/10.1063/5.0063690 | DOI Listing |
Med Biol Eng Comput
January 2025
Faculty of Computing, Harbin Institute of Technology, Harbin, 150001, China.
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based method which performs more effectively in cases involving artifacts or plaques.
View Article and Find Full Text PDFMed Phys
January 2025
National Institute for Mathematical Sciences, Daejeon, Republic of Korea.
Background: In X-ray computed tomography (CT), metal-induced beam hardening artifacts arise from the complex interactions between polychromatic X-ray beams and metallic objects, leading to degraded image quality and impeding accurate diagnosis. A previously proposed metal-induced beam hardening correction (MBHC) method provides a theoretical framework for addressing nonlinear artifacts through mathematical analysis, with its effectiveness demonstrated by numerical simulations and phantom experiments. However, in practical applications, this method relies on precise segmentation of highly attenuating materials and parameter estimations, which limit its ability to fully correct artifacts caused by the intricate interactions between metals and other dense materials, such as bone or teeth.
View Article and Find Full Text PDFMagn Reson Med
January 2025
F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.
Purpose: The present work aims to evaluate the performance of three-dimensional (3D) single-shot stack-of-spirals turbo FLASH (SOS-TFL) acquisition for pseudo-continuous arterial spin labeling (PCASL) and velocity-selective ASL (VSASL)-based cerebral blood flow (CBF) mapping, as well as VSASL-based cerebral blood volume (CBV) mapping.
Methods: Digital phantom simulations were conducted for both multishot echo planar imaging and spiral trajectories with intershot signal fluctuations. PCASL-derived CBF (PCASL-CBF), VSASL-derived CBF (VSASL-CBF), and CBV (VSASL-CBV) were all acquired using 3D multishot gradient and spin-echo and SOS-TFL acquisitions following background suppression.
Magn Reson Med
January 2025
C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
Purpose: To evaluate accelerated T- and T-mapping techniques for ultra-low-field MRI using low-rank reconstruction methods.
Methods: Two low-rank-based algorithms, image-based locally low-rank (LLR) and k-space-based structured low-rank (SLR), were implemented to accelerate T and T mapping on a 46 mT Halbach MRI scanner. Data were acquired with 3D turbo spin-echo sequences using variable-density poisson-disk random sampling patterns.
Sci Rep
January 2025
Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability and classification accuracy.
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