The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) scheme is proposed to assist radiologists in the differentiation of lung patterns associated with ILD and healthy lung parenchyma. Regions of interest were described by a set of texture attributes extracted using differential lacunarity (DLac) and classical methods of statistical texture analysis. The proposed strategy to compute DLac allowed a multiscale texture analysis, while maintaining sensitivity to small details. Support Vector Machines were employed to distinguish between lung patterns. Training and model selection were performed over a stratified 10-fold cross-validation (CV). Dimensional reduction was made based on stepwise regression (F-test, p value < 0.01) during CV. An accuracy of 95.8 ± 2.2% in the differentiation of normal lung pattern from ILD patterns and an overall accuracy of 94.5 ± 2.1% in a multiclass scenario revealed the potential of the proposed CAD in clinical practice. Experimental results showed that the performance of the CAD was improved by combining multiscale DLac with classical statistical texture analysis.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700165 | PMC |
| http://dx.doi.org/10.1155/2015/672520 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Robust Multi-Subtype Identification of Breast Cancer Pathological Images Based on a Dual-Branch Frequency Domain Fusion Network.
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 PDFSeasonal Land Use and Land Cover Mapping in South American Agricultural Watersheds Using Multisource Remote Sensing: The Case of Cuenca Laguna Merín, Uruguay.
Sensors (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.
View Article and Find Full Text PDFMultiscale Residual Weighted Classification Network for Human Activity Recognition in Microwave Radar.
Sensors (Basel)
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 PDFVegetable-Enriched Brownies: A Healthier Twist on a Classic Treat.
Nutrients
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.
High-Pressure Treatment in Combination with Reduced Sodium for Improving the Physicochemical Properties and Sensory Qualities of Pork Gels.
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.
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!