Articles
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91 results found
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Computer vision
Computer vision is a field concerned with the creation of generalized automated computer insight into visual data i.e. making computers see. Although often understood as a field within computer science, the field actually involves work in informatics, various fields of engineering and neuroscien...
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Artificial intelligence
Artificial intelligence (AI) has been defined by some as the "branch of computer science dealing with the simulation of intelligent behavior in computers" 1, however, the precise definition is a matter of debate among experts.
An alternative definition is the branch of computer science dedicat...
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Computer aided diagnosis
Computer aided diagnosis (CAD) is the use of a computer generated output as an assisting tool for a clinician to make a diagnosis. It is different from automated computer diagnosis, in which the end diagnosis is based on a computer algorithm only.
As an early form of artificial intelligence, co...
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Python (programming language)
Python is a high-level, general-purpose computer programming language. Initially, Python was created by Dutch computer programmer Guido van Rossum and was first released in 1991. The version 3.7.4 (which is the most stable release as of July 2019) Python language has objects and associated mach...
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METhodological RadiomICs Score (METRICS)
The METhodological RadiomICs Score (METRICS) is a 30-item quality evaluation tool for artificial intelligence (AI) and radiomics papers 1. It aims to assess and improve the quality of radiomics research. METRICS is endorsed by the European Society of Medical Imaging Informatics (EuSoMII).
Overv...
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Segmentation
Segmentation, in the context of informatics for radiology, refers to the delineation of areas of interest in imaging in terms of pixels or voxels.
Segmentation is often accomplished by computerized algorithms that vary in complexity from simply selecting pixels of similar values in proximity to...
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Radiomics
Radiomics (as applied to radiology) is a field of medical study that aims to extract a large number of quantitative features from medical images using data characterization algorithms. The data is assessed for improved decision support. It has the potential to uncover disease characteristics tha...
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Machine learning
Machine learning is a specific practical application of computer science and mathematics that allows computers to extrapolate information based on observed patterns without explicit programming. A defining characteristic of machine learning programs is the improved performance at tasks such as c...
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CheckList for EvaluAtion of Radiomics research (CLEAR)
The CheckList for Evaluation of Radiomics Research (CLEAR) is a 58-item reporting guideline designed specifically for radiomics. It aims to improve the quality of reporting in radiomics research 1. CLEAR is endorsed by the European Society of Radiology (ESR) and the European Society of Medical I...
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Image normalization
Image normalization is a process, often used in the preparation of data sets for artificial intelligence (AI), in which multiple images are put into a common statistical distribution in terms of size and pixel values; however, a single image can also be normalized within itself. The process usua...
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Imaging data sets (artificial intelligence)
The aggregation of an imaging data set is a critical step in building artificial intelligence (AI) for radiology. Imaging data sets are used in various ways including training and/or testing algorithms. Many data sets for building convolutional neural networks for image identification involve at...
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Explainable artificial intelligence
Explainable artificial intelligence usually refers to narrow artificial intelligence models made with methods that enable and enhance human understanding of how the models reached outputs in each case. Many older AI models, e.g. decision trees, were inherently understandable in terms of how they...
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Bayes' theorem
Bayes' theorem, also known as Bayes' rule or Bayes' law, is a theorem in statistics that describes the probability of one event or condition as it relates to another known event or condition. Mathematically, the theory can be expressed as follows: P(A|B) = (P(B|A) x P(A) )/P(B), where given that...
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Convolutional neural network
A convolutional neural network (CNN) is a particular implementation of a neural network used in deep learning that exclusively processes array data such as images, and is thus frequently used in machine learning applications targeted at medical images 1.
Architecture
A convolutional neural net...
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ImageNet dataset
The ImageNet is an extensive image database that has been instrumental in advancing computer vision and deep learning research. It contains more than 14 million, hand-annotated images classified into more than 20,000 categories. In at least one million of the images, bounding boxes are also prov...
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Large language models
Large language models are advanced artificial intelligence systems designed to understand and generate human-like text. These models are built using deep learning techniques and are trained on vast amounts of text data, such as books, articles, and websites. Large language models utilize algorit...
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Natural language processing
Natural language processing (NLP) is an area of active research in artificial intelligence concerned with human languages. Natural language processing programs use human written text or human speech as data for analysis. The goals of natural language processing programs can vary from generating ...
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Hebbian learning
Hebbian learning describes a type of activity-dependent modification of the strength of synaptic transmission at pre-existing synapses which plays a central role in the capacity of the brain to convert transient experiences into memory. According to Hebb et al 1, two cells or systems of cells th...
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Convolution
Convolution is a mathematical concept that implies the product of two functions. In practical terms for radiology, convolution implies the application of a mathematical operation to a signal such that a different signal is produced. Convolutions are applied in image processing for CTs and MRIs.
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Bayes' factor
A Bayes' factor is a number that quantifies the relative likelihood of two models or hypotheses to each other if made into a ratio e.g. if two models are equally likely based on the prior evidence ( or there is no prior evidence) then the Bayes factor would be one.
Such factors have several use...
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