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In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder.
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on this page show how higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression which does not degrade the data. The amount of data reduction possible using lossy compression is much higher than using lossless techniques.
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Radiology is the medical discipline that uses medical imaging to diagnose diseases and guide their treatment, within the bodies of humans and other animals. It began with radiography, but today it includes all imaging modalities, including those that use no electromagnetic radiation, as well as others that do, such as computed tomography (CT), fluoroscopy, and nuclear medicine including positron emission tomography (PET). Interventional radiology is the performance of usually minimally invasive medical procedures with the guidance of imaging technologies such as those mentioned above.
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 data compression and psychoacoustics, transparency is the result of lossy data compression accurate enough that the compressed result is perceptually indistinguishable from the uncompressed input, i.e. perceptually lossless.
Peak signal-to-noise ratio (PSNR) is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation. Because many signals have a very wide dynamic range, PSNR is usually expressed as a logarithmic quantity using the decibel scale.
Video quality is a characteristic of a video passed through a video transmission or processing system that describes perceived video degradation. Video processing systems may introduce some amount of distortion or artifacts in the video signal that negatively impacts the user's perception of a system. For many stakeholders in video production and distribution, assurance of video quality is an important task.
Teleradiology is the transmission of radiological patient images, such as x-rays, CTs, and MRIs, from one location to another for the purposes of sharing studies with other radiologists and physicians. Teleradiology is a growth technology given that imaging procedures are growing approximately 15% annually against an increase of only 2% in the radiologist population.
The structural similarityindex measure (SSIM) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. SSIM is used for measuring the similarity between two images. The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference.
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, Endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time. CAD systems process digital images or videos for typical appearances and to highlight conspicuous sections, such as possible diseases, in order to offer input to support a decision taken by the professional.
Image quality can refer to the level of accuracy with which different imaging systems capture, process, store, compress, transmit and display the signals that form an image. Another definition refers to image quality as "the weighted combination of all of the visually significant attributes of an image". The difference between the two definitions is that one focuses on the characteristics of signal processing in different imaging systems and the latter on the perceptual assessments that make an image pleasant for human viewers.
The MOtion-tuned Video Integrity Evaluation (MOVIE) index is a model and set of algorithms for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos.
Video Multimethod Assessment Fusion (VMAF) is an objective full-reference video quality metric developed by Netflix in cooperation with the University of Southern California, The IPI/LS2N lab Nantes Université, and the Laboratory for Image and Video Engineering (LIVE) at The University of Texas at Austin. It predicts subjective video quality based on a reference and distorted video sequence. The metric can be used to evaluate the quality of different video codecs, encoders, encoding settings, or transmission variants.
JPEG XT is an image compression standard which specifies backward-compatible extensions of the base JPEG standard.
JPEG XS is an interoperable, visually lossless, low-latency and lightweight image and video coding system used in professional applications. Applications of the standard include streaming high quality content for virtual reality, drones, autonomous vehicles using cameras, gaming, and broadcasting. In this respect, JPEG XS is unique, being the first ISO codec ever designed for this specific purpose. JPEG XS, built on core technology from both intoPIX and Fraunhofer IIS, is formally standardized as ISO/IEC 21122 by the Joint Photographic Experts Group with the first edition published in 2019. Although not official, the XS acronym was chosen to highlight the eXtra Small and eXtra Speed characteristics of the codec. Today, the JPEG committee is still actively working on further improvements to XS, with the second edition scheduled for publication and initial efforts being launched towards a third edition.
Elastix is an image registration toolbox built upon the Insight Segmentation and Registration Toolkit (ITK). It is entirely open-source and provides a wide range of algorithms employed in image registration problems. Its components are designed to be modular to ease a fast and reliable creation of various registration pipelines tailored for case-specific applications. It was first developed by Stefan Klein and Marius Staring under the supervision of Josien P.W. Pluim at Image Sciences Institute (ISI). Its first version was command-line based, allowing the final user to employ scripts to automatically process big data-sets and deploy multiple registration pipelines with few lines of code. Nowadays, to further widen its audience, a version called SimpleElastix is also available, developed by Kasper Marstal, which allows the integration of elastix with high level languages, such as Python, Java, and R.
Video super-resolution (VSR) is the process of generating high-resolution video frames from the given low-resolution video frames. Unlike single-image super-resolution (SISR), the main goal is not only to restore more fine details while saving coarse ones, but also to preserve motion consistency.
Sergey Pavlovich Morozov is a Russian radiologist and healthcare official.
References
- 1 2 3 4 European Society of Radiology (April 2011). "Usability of irreversible image compression in radiological imaging. A position paper by the European Society of Radiology (ESR)". Insights into Imaging. 2 (2): 103–115. doi: 10.1007/s13244-011-0071-x . PMC 3259360 . PMID 22347940.
- ↑ Richter, Thomas (September 2016). "JPEG on STEROIDS: Common optimization techniques for JPEG image compression". 2016 IEEE International Conference on Image Processing (ICIP). pp. 61–65. doi:10.1109/ICIP.2016.7532319. ISBN 978-1-4673-9961-6. S2CID 14922251.
- ↑ Renieblas, Gabriel Prieto; Nogués, Agustín Turrero; González, Alberto Muñoz; Gómez-Leon, Nieves; del Castillo, Eduardo Guibelalde (26 July 2017). "Structural similarity index family for image quality assessment in radiological images". Journal of Medical Imaging. 4 (3): 035501. doi:10.1117/1.JMI.4.3.035501. PMC 5527267 . PMID 28924574.
- ↑ Mason, A; Rioux, J; Clarke, SE; Costa, A; Schmidt, M; Keough, V; Huynh, T; Beyea, S (April 2020). "Comparison of Objective Image Quality Metrics to Expert Radiologists' Scoring of Diagnostic Quality of MR Images". IEEE Transactions on Medical Imaging. 39 (4): 1064–1072. doi: 10.1109/TMI.2019.2930338 . PMID 31535985.
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