Information engineering in the context of "Medical image analysis"

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⭐ Core Definition: Information engineering

Information engineering is the engineering discipline that deals with the generation, distribution, analysis, and use of information, data, and knowledge in electrical systems. The field first became identifiable in the early 21st century.

The components of information engineering include more theoretical fields such as electromagnetism, machine learning, artificial intelligence, control theory, signal processing, and microelectronics, and more applied fields such as computer vision, natural language processing, bioinformatics, medical image computing, cheminformatics, autonomous robotics, mobile robotics, and telecommunications. Many of these originate from computer engineering, as well as other branches of engineering such as electrical engineering, computer science and bioengineering.

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👉 Information engineering in the context of Medical image analysis

Medical image computing (MIC) is the use of computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care. It is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine.

The main goal of MIC is to extract clinically relevant information or knowledge from medical images. While closely related to the field of medical imaging, MIC focuses on the computational analysis of the images, not their acquisition. The methods can be grouped into several broad categories: image segmentation, image registration, image-based physiological modeling, and others.

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Information engineering in the context of Bioinformatics

Bioinformatics (/ˌb.ˌɪnfərˈmætɪks/ ) is an interdisciplinary field of science that develops computational methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, data science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. This process can sometimes be referred to as computational biology, however the distinction between the two terms is often disputed. To some, the term computational biology refers to building and using models of biological systems.

Computational, statistical, and computer programming techniques have been used for computer simulation analyses of biological queries. They include reused specific analysis "pipelines", particularly in the field of genomics, such as by the identification of genes and single nucleotide polymorphisms (SNPs). These pipelines are used to better understand the genetic basis of disease, unique adaptations, desirable properties (especially in agricultural species), or differences between populations. Bioinformatics also includes proteomics, which aims to understand the organizational principles within nucleic acid and protein sequences.

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Information engineering in the context of Mobile robots

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering.

Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" (AMR - autonomous mobile robot) which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices. Alternatively, mobile robots can rely on guidance devices that allow them to travel a pre-defined navigation route in relatively controlled space. By contrast, industrial robots are usually more-or-less stationary, consisting of a jointed arm (multi-linked manipulator) and gripper assembly (or end effector), attached to a fixed surface. The joint.

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