Description: Volumetric data are representations of a three-dimensional space that allow modeling and analyzing phenomena in various disciplines, such as physics, medicine, and engineering. These data are structured in a three-dimensional grid, where each point in the grid, known as a voxel (volumetric pixel), contains information about a specific property of the space, such as density, temperature, or color intensity. This representation is fundamental in scientific computing and simulations, as it enables effective visualization and manipulation of complex data. Volumetric data are particularly useful in applications that require detailed analysis of three-dimensional structures, such as in computed tomography, where images are generated from volumetric data to diagnose diseases. Additionally, their use has expanded into areas like virtual and augmented reality, where accurate representation of the three-dimensional environment is needed to create immersive experiences. The ability to process and analyze this data has significantly improved with the advancement of technologies such as machine learning and convolutional neural networks, which allow for the extraction of relevant patterns and features from large volumes of three-dimensional data.
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