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Udupa has worked in the fields of medical image science, image processing, and physics analysis of medical imaging and medical diagnostic procedures since the 1980s. He is known for his contributions in image processing [ 2 ] and its applications in various fields of science, medicine, and engineering.
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.
Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. [1]
If the goal is a medical diagnostic, then histology applications will often fall into the realm of digital pathology or automated tissue image analysis, which are sister fields of bioimage informatics. The same computational techniques are often applicable, but the goals are medically- rather than research-oriented.
Dimitri Van De Ville (born 1975 in Dendermonde) is a Swiss and Belgian computer scientist and neuroscientist specialized in dynamical and network aspects of brain activity.He is a professor of bioengineering at EPFL (École Polytechnique Fédérale de Lausanne) and the head of the Medical Image Processing Laboratory at EPFL's School of Engineering.
Information Processing in Medical Imaging, or IPMI, is a conference held every two years [1] focused on the fields of applied mathematics, computer science, image processing and image analysis (particularly of medical images); applied results in neuroscience, cardiology, and microscopy are also frequently considered. IPMI is the longest ...
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
The program has its origins in the non-NIH funded MD-PhD training offered at the nation's research-centric medical schools. An early dual-degree program began at Case Western Reserve University School of Medicine in 1956. [4] Other prominent medical schools quickly followed this example and developed integrated MD-PhD training structures.