Since the beginning of the industrial revolution, manufacturing has gone through different stages: the 1st technological islands, 2nd the mass production, 3rd the lean manufacturing and the 4th IIoT (for the year 2025); we must keep in mind the leadership in the production of goods today what the Eastern countries have (and are using stage 3), so that the current guidelines have the necessary meaning, which establishes a new way of producing more as the potential of technologies that are in the process of maturation such as: Artificial Intelligence, Big Data, 3D Printing and Robotics; find original solutions to the problems of productivity, customization, just in time and services.Artificial Intelligence is taking a leading role in solving manufacturing problems, with the purpose of eliminating all those areas that are blindly worked, and that therefore it is not possible to improve by suffering from data to: analyze them, obtain information, establish controls and improve. The above is achieved by establishing disruptive technologies that take control in real time.
Electron Tomography (ET) is a powerful three-dimensional (3D) imaging technique used in structural biology and biomedicine to allow the visualization of the interior of cells at close-to-molecular resolution. Interpretation of the 3D volumes in ET is usually challenging due to the complexity of the cellular environment, noise conditions and other factors. Automated segmentation methods focused on membranes of the cells and organelles greatly facilitate visualization and interpretation of the 3D volumes. However, they are typically computationally expensive and spend significant processing time on standard computers. In this work, we introduce efficient implementations of one of the methods most commonly used in the ET field for membrane segmentation. They were developed by using High Performance Computing (HPC) techniques to make the most of modern CPU-based and GPU-based computing platforms. A thorough evaluation of the performance on state-of-the-art machines was carried out. The HPC implementations succeed in achieving remarkable speedups, which are around 100× on GPUs, and making it possible to process large 3D volumes in the order of seconds or a few minutes.
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