Detection of region specific voxel is a true challenge in many segmentation procedures. In this study a concept of implementing granular computing in the detection of anatomical structures in abdominal computed tomography (CT) scans is introduced. After proving the usefulness of the information granules to identify voxels that mark certain organs, an automatic model-based approach has been developed. A three-parameter granule that combines the interval and density distribution of voxels has been introduced and employed to identify organ specific voxels of the liver, spleen and kidneys. The specificity of the information granules varies between 90 and 99% for the liver and spleen and over 85% for the kidneys.
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http://dx.doi.org/10.1016/j.compmedimag.2015.03.002 | DOI Listing |
Data Brief
December 2024
School of Computing, Dublin City University, Dublin, Ireland.
Research in field sports often measures the performance of players during competitive games with individual and time-based descriptive statistics. Data is generated using GPS technologies, capturing simple data such as time (seconds) and position (latitude and longitude). While the data capture is highly granular and in relatively high volumes, the raw data are unsuited to any form of analysis or machine learning functions.
View Article and Find Full Text PDFPLoS Comput Biol
December 2024
Institute of Software Technology, Department of High-Performance Computing, German Aerospace Center, Cologne, Germany.
In the realm of infectious disease control, accurate modeling of the transmission dynamics is pivotal. As human mobility and commuting patterns are key components of communicable disease spread, we introduce a novel travel time aware metapopulation model. Our model aims to enhance estimations of disease transmission.
View Article and Find Full Text PDFCalc Var Partial Differ Equ
May 2024
Institute of Scientific Computing, Technische Universität Dresden, Zellescher Weg 12-14, 01069 Dresden, Germany.
The aggregation equation arises naturally in kinetic theory in the study of granular media, and its interpretation as a 2-Wasserstein gradient flow for the nonlocal interaction energy is well-known. Starting from the spatially homogeneous inelastic Boltzmann equation, a formal Taylor expansion reveals a link between this equation and the aggregation equation with an appropriately chosen interaction potential. Inspired by this formal link and the fact that the associated aggregation equation also dissipates the kinetic energy, we present a novel way of interpreting the aggregation equation as a gradient flow, in the sense of curves of maximal slope, of the kinetic energy, rather than the usual interaction energy, with respect to an appropriately constructed transportation metric on the space of probability measures.
View Article and Find Full Text PDFNeural Netw
December 2024
National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China; Medical UltraSound Image Computing (MUSIC) Lab, Shenzhen University, Shenzhen, China; Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China. Electronic address:
Interactive segmentation allows active user participation to enhance output quality and resolve ambiguities. This may be especially indispensable to medical image segmentation to address complex anatomy and customization to varying user requirements. Existing approaches often encounter issues such as information dilution, limited adaptability to diverse user interactions, and insufficient response.
View Article and Find Full Text PDFBMC Med Res Methodol
November 2024
Centre for Health Informatics, Computing, and Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
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