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Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.
An MIT-led research team has crafted a machine learning algorithm that can analyze 3D scans up to 1,000 times faster than before, making it possible to study changes almost in real time -- less ...
Computational imaging systems span a broad range of applications. While applications such as SAR, computed tomography, seismic inversion are well known, they have undergone significant improvements (faster, higher-resolution, lower dose exposures [3]) driven by advances in signal and image processing algorithms (including compressed sensing techniques), and faster computing platforms.
MeVisLab – cross-platform software for medical image processing and visualization (based on OpenGL and Open Inventor) Open Inventor – a high-level 3D API for 3D graphics software development (C++, .NET, Java) ScanIP – an image processing and image-based meshing platform that can render scan data (MRI, CT, Micro-CT...) in 3D directly after ...
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The future development of these technologies is advantageous as it gives a solution to human limitations in medical image processing. [4] Although a highly accurate and fully automated CAD system has yet to be realized, recent advancements in Artificial Intelligence may allow for functioning implementations. [11]
Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues . Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease.
Ron Kikinis is an American physician and scientist best known for his research in the fields of imaging informatics, image guided surgery, and medical image computing.He is a professor of radiology at Harvard Medical School.