A picture archiving and communication system (PACS) is a medical imaging technology which provides economical storage and convenient access to images from multiple modalities. Electronic images and reports are transmitted digitally via PACS; this eliminates the need to manually file, retrieve, or transport film jackets, the folders used to store and protect X-ray film. The universal format for PACS image storage and transfer is DICOM. Non-image data, such as scanned documents, may be incorporated using consumer industry standard formats like PDF, once encapsulated in DICOM. A PACS consists of four major components: The imaging modalities such as X-ray plain film (PF), computed tomography (CT) and magnetic resonance imaging (MRI), a secured network for the transmission of patient information, workstations for interpreting and reviewing images, and archives for the storage and retrieval of images and reports. Combined with available and emerging web technology, PACS has the ability to deliver timely and efficient access to images, interpretations, and related data. PACS reduces the physical and time barriers associated with traditional film-based image retrieval, distribution, and display.
Digital Imaging and Communications in Medicine (DICOM) is the standard for the communication and management of medical imaging information and related data. DICOM is most commonly used for storing and transmitting medical images enabling the integration of medical imaging devices such as scanners, servers, workstations, printers, network hardware, and picture archiving and communication systems (PACS) from multiple manufacturers. It has been widely adopted by hospitals and is making inroads into smaller applications such as dentists' and doctors' offices.
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. It is used in computer vision, medical imaging, military automatic target recognition, and compiling and analyzing images and data from satellites. Registration is necessary in order to be able to compare or integrate the data obtained from these different measurements.
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 (physiology). Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities. Although imaging of removed organs and tissues can be performed for medical reasons, such procedures are usually considered part of pathology instead of medical imaging.
In scientific visualization and computer graphics, volume rendering is a set of techniques used to display a 2D projection of a 3D discretely sampled data set, typically a 3D scalar field.
ITK is a cross-platform, open-source application development framework widely used for the development of image segmentation and image registration programs. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with an MRI scan in order to combine the information contained in both.
ITK-SNAP is an interactive software application that allows users to navigate three-dimensional medical images, manually delineate anatomical regions of interest, and perform automatic image segmentation. The software was designed with the audience of clinical and basic science researchers in mind, and emphasis has been placed on having a user-friendly interface and maintaining a limited feature set to prevent feature creep. ITK-SNAP is most frequently used to work with magnetic resonance imaging (MRI), cone-beam computed tomography (CBCT) and computed tomography (CT) data sets.
3D Slicer (Slicer) is a free and open source software package for image analysis and scientific visualization. Slicer is used in a variety of medical applications, including autism, multiple sclerosis, systemic lupus erythematosus, prostate cancer, lung cancer, breast cancer, schizophrenia, orthopedic biomechanics, COPD, cardiovascular disease and neurosurgery.
Image-based meshing is the automated process of creating computer models for computational fluid dynamics (CFD) and finite element analysis (FEA) from 3D image data. Although a wide range of mesh generation techniques are currently available, these were usually developed to generate models from computer-aided design (CAD), and therefore have difficulties meshing from 3D imaging data.
Synopsys Simpleware ScanIP is a 3D image processing and model generation software program developed by Synopsys Inc. to visualise, analyse, quantify, segment and export 3D image data from magnetic resonance imaging (MRI), computed tomography (CT), microtomography and other modalities for computer-aided design (CAD), finite element analysis (FEA), computational fluid dynamics (CFD), and 3D printing. The software is used in the life sciences, materials science, nondestructive testing, reverse engineering and petrophysics.
Industrial computed tomography (CT) scanning is any computer-aided tomographic process, usually X-ray computed tomography, that uses irradiation to produce three-dimensional internal and external representations of a scanned object. Industrial CT scanning has been used in many areas of industry for internal inspection of components. Some of the key uses for industrial CT scanning have been flaw detection, failure analysis, metrology, assembly analysis and reverse engineering applications. Just as in medical imaging, industrial imaging includes both nontomographic radiography and computed tomographic radiography.
GIMIAS is a workflow-oriented environment focused on biomedical image computing and simulation. The open-source framework is extensible through plug-ins and is focused on building research and clinical software prototypes. Gimias has been used to develop clinical prototypes in the fields of cardiac imaging and simulation, angiography imaging and simulation, and neurology
MeVisLab is a cross-platform application framework for medical image processing and scientific visualization. It includes advanced algorithms for image registration, segmentation, and quantitative morphological and functional image analysis. An IDE for graphical programming and rapid user interface prototyping is available.
Materialise NV, headquartered in Leuven, Belgium, is a company in the 3D printing / additive manufacturing sector.
IMOD is an open-source, cross-platform suite of modeling, display and image processing programs used for 3D reconstruction and modeling of microscopy images with a special emphasis on electron microscopy data. IMOD has been used across a range of scales from macromolecule structures to organelles to whole cells and can also be used for optical sections. IMOD includes tools for image reconstruction, image segmentation, 3D mesh modeling and analysis of 2D and 3D data.
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.
Amira is a software platform for 3D and 4D data visualization, processing, and analysis. It is being actively developed by Thermo Fisher Scientific in collaboration with the Zuse Institute Berlin (ZIB), and commercially distributed by Thermo Fisher Scientific.
A digital autopsy is a non-invasive autopsy in which digital imaging technology, such as with Computerized Tomography (CT) or Magnetic Resonance Imaging (MRI) scans, is used to develop three-dimensional images for a virtual exploration of a human body.
Studierfenster or StudierFenster (SF) is a free, non-commercial open science client/server-based medical imaging processing online framework. It offers capabilities, like viewing medical data (computed tomography (CT), magnetic resonance imaging (MRI), etc.) in two- and three-dimensional space directly in standard web browsers, like Google Chrome, Mozilla Firefox, Safari, and Microsoft Edge. Other functionalities are the calculation of medical metrics (dice score and Hausdorff distance), manual slice-by-slice outlining of structures in medical images (segmentation), manual placing of (anatomical) landmarks in medical image data, viewing medical data in virtual reality, a facial reconstruction and registration of medical data for augmented reality, one click showcases for COVID-19 and veterinary scans, and a Radiomics module.
