Susceptibility-weighted imaging (SWI) has been used to identify neurodegeneration in amyotrophic lateral sclerosis (ALS) through qualitative gross visual comparison of signal intensity. The aim of this study was to quantitatively identify cerebral degeneration in ALS on SWI using texture analysis. SW images were acquired from 17 ALS patients (58.4 ± 10.3 years, 13M/4F, ALSFRS-R 41.2 ± 4.1) and 18 healthy controls (56.3 ± 17.6 years, 9M/9F) at 4.7 tesla. Textures were computed within the precentral gyrus and basal ganglia and compared between patients and controls using ANCOVA with age and gender as covariates. Texture features were correlated with clinical measures in patients. Texture features found to be significantly different between patients and controls in the precentral gyrus were then used in a whole-brain 3D texture analysis. The texture feature autocorrelation was significantly higher in ALS patients compared to healthy controls in the precentral gyrus and basal ganglia ( < 0.05). Autocorrelation correlated significantly with clinical measures such as disease progression rate and finger tapping speed ( < 0.05). Whole brain 3D texture analysis using autocorrelation revealed differences between ALS patients and controls within the precentral gyrus on SWI images ( < 0.001). Texture analysis on SWI can quantitatively identify cerebral differences between ALS patients and controls.
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http://dx.doi.org/10.1080/21678421.2019.1599024 | DOI Listing |
Sensors (Basel)
January 2025
School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.
Breast cancer (BC) is one of the most lethal cancers worldwide, and its early diagnosis is critical for improving patient survival rates. However, the extraction of key information from complex medical images and the attainment of high-precision classification present a significant challenge. In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Departamento de Geografía, Facultad de Ciencias, Universidad de la República, Montevideo 4225, Uruguay.
Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers.
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January 2025
School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China.
Human activity recognition by radar sensors plays an important role in healthcare and smart homes. However, labeling a large number of radar datasets is difficult and time-consuming, and it is difficult for models trained on insufficient labeled data to obtain exact classification results. In this paper, we propose a multiscale residual weighted classification network with large-scale, medium-scale, and small-scale residual networks.
View Article and Find Full Text PDFNutrients
January 2025
Department of Plant Products Technology and Nutrition Hygiene, Faculty of Food Technology, University of Agriculture in Krakow, 21 Mickiewicz Av., 31-120 Krakow, Poland.
Background/objectives: In response to concerns about high-fat and low-fiber diets, this study modified a traditional brownie recipe by replacing butter with plant-based ingredients, including sweet potatoes, red beans, beetroot, zucchini, pumpkin, lentils, and spinach. The goal was to increase vegetable consumption while identifying the best vegetable fat replacer using sensory and instrumental analyses.
Methods: Chemical analyses were conducted to measure dry matter, protein, fat, ash, and dietary fiber, alongside texture, color, and sensory evaluations.
Foods
January 2025
Graduate School of Science and Technology, Niigata University, 8050 Ikarashi 2 nocho, Nishi-ku, Niigata 950-2181, Japan.
High-pressure treatment was utilized in this study to produce high-quality, reduced-sodium pork gels with desirable texture and sensory properties, addressing the challenge of maintaining quality in low-sodium meat products to meet health-conscious consumer demands. High-pressure treatment applied within the range of 150-200 MPa significantly reduced cooking loss while maintaining moisture content and provided an ideal network structure for reduced-sodium pork gels. High-pressure treatment at up to 100-200 MPa, in combination with added sodium chloride and sodium polyphosphate, was evaluated for its effects on gel texture, with results indicating that high-pressure treatment significantly improved breaking stress (increased by 10.
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