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Medical Image Analysis (MedIA) is a peer-reviewed academic journal which focuses on medical and biological image analysis.The journal publishes papers which contribute to the basic science of analyzing and processing biomedical images acquired through means such as magnetic resonance imaging, ultrasound, computed tomography, nuclear medicine, x-ray, optical and confocal microscopy, among others.
Medical image segmentation is made difficult by low contrast, noise, and other imaging ambiguities. Although there are many computer vision techniques for image segmentation, some have been adapted specifically for medical image computing. Below is a sampling of techniques within this field; the implementation relies on the expertise that ...
Higher SJR indicator values are meant to indicate greater journal prestige. SJR is developed by the Scimago Lab, [5] originated from a research group at the University of Granada. The SJR indicator is a variant of the eigenvector centrality measure used in network theory. Such measures establish the importance of a node in a network based on ...
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.
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The journal covers research in computer vision and image understanding, pattern analysis and recognition, machine intelligence, machine learning, search techniques, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, and face and gesture recognition.
DICOM is used worldwide to store, exchange, and transmit medical images.DICOM has been central to the development of modern radiological imaging: DICOM incorporates standards for imaging modalities such as radiography, ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and radiation therapy.
As a result, the main limiting factor for the medical imaging field became the human inability to accurately interpret large amounts of data. [4] Thus, the need arose for computerized assistance with complex digital imaging analysis, storage and manipulation. Modern Imaging Informatics was developed to fulfill these needs.