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Cryo-electron microscopy (cryoEM) has become a popular method for determining high-resolution structures of biomolecules. However, data processing can be time-consuming, particularly for new researchers entering the field. To improve data quality and increase data collection efficiency, several software packages have been developed for on-the-fly data processing with various degrees of automation. These software packages allow researchers to perform tasks such as motion correction, CTF estimation, 2D classification, and 3D reconstruction in real-time, with minimal human input. On-the-fly data processing can not only improve data collection efficiency but also increase the productivity of instrumentation in high demand. However, the various software packages available differ in their performance, computational requirements, and levels of automation. In this review, we describe the minimal metrics used to assess data quality during data collection, outline the features of an ideal on-the-fly data processing software systems, and provide results from using three of these systems.
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http://dx.doi.org/10.1016/j.sbi.2023.102729 | DOI Listing |
Hum Brain Mapp
December 2024
Department of Psychology, Northeastern University, Boston, Massachusetts, USA.
Diffusion-weighted imaging (DWI) has been frequently used to examine age-related deterioration of white matter microstructure and its relationship to cognitive decline. However, typical tensor-based analytical approaches are often difficult to interpret due to the challenge of decomposing and (mis)interpreting the impact of crossing fibers within a voxel. We hypothesized that a novel analytical approach capable of resolving fiber-specific changes within each voxel (i.
View Article and Find Full Text PDFFront Public Health
December 2024
School of Management Engineering and Business, Hebei University of Engineering, Handan, China.
In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a population of 276 million, accounting for over 20% of the total population, making significant contributions to urban economic development and resource optimization. However, the health status of migrant populations is affected by unique issues such as occupational risks and socio-economic disparities, which play an important role in personal welfare, social stability, and sustainable economic growth.
View Article and Find Full Text PDFFront Cell Infect Microbiol
December 2024
Center for Microbial Pathogenesis, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, United States.
Introduction: Typhoid fever is an infectious disease primarily caused by sv. Typhi ( Typhi), a bacterium that causes as many as 20 million infections and 600,000 deaths annually. Asymptomatic chronic carriers of S.
View Article and Find Full Text PDFHealthc Technol Lett
December 2024
Despite the benefits of minimally invasive surgery, interventions such as laparoscopic liver surgery present unique challenges, like the significant anatomical differences between preoperative images and intraoperative scenes due to pneumoperitoneum, patient pose, and organ manipulation by surgical instruments. To address these challenges, a method for intraoperative three-dimensional reconstruction of the surgical scene, including vessels and tumors, without altering the surgical workflow, is proposed. The technique combines neural radiance field reconstructions from tracked laparoscopic videos with ultrasound three-dimensional compounding.
View Article and Find Full Text PDFThis study investigates the reconstruction of hyperspectral signatures from RGB data to enhance surgical imaging, utilizing the publicly available HeiPorSPECTRAL dataset from porcine surgery and an in-house neurosurgery dataset. Various architectures based on convolutional neural networks (CNNs) and transformer models are evaluated using comprehensive metrics. Transformer models exhibit superior performance in terms of RMSE, SAM, PSNR and SSIM by effectively integrating spatial information to predict accurate spectral profiles, encompassing both visible and extended spectral ranges.
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