The graph illustrates the most common radiology procedures at imaging centers in the U.S. in 2018, by total charges. During that year, total charges for an MRI of the neck without dye at imaging centers amounted to around 362.2 million U.S. dollars.

Background

The COVID-19 pandemic is a global healthcare emergency. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making in imaging. However, inadequate availability of a diverse annotated dataset has limited the performance and generalizability of existing models.

Purpose

To create the first multi-institutional, multi-national expert annotated COVID-19 imaging dataset made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. The Radiological Society of North America (RSNA) assembled the RSNA International COVID-19 Open Radiology Database (RICORD) collection of COVID-related imaging datasets and expert annotations to support research and education. RICORD data will be incorporated in the Medical Imaging and Data Resource Center (MIDRC), a multi-institutional research data repository funded by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health.

Materials and Methods

This dataset was a collaboration between the RSNA and Society of Thoracic Radiology (STR).

Results

The RSNA International COVID-19 Open Annotated Radiology Database (RICORD) release 1b consists of 120 thoracic computed tomography (CT) scans of COVID negative patients from four international sites.

Patient Selection: Patients at least 18 years in age receiving negative diagnosis for COVID-19.

Data Abstract

1. 120 de-identified Thoracic CT scans from COVID negative patients.

2. Supporting clinical variables: MRN*, Age, Exam Date/Time*, Exam Description, Sex, Study UID*, Image Count, Modality, Symptomatic, Testing Result, Specimen Source (* pseudonymous values).

Research Benefits

As this is a public dataset, RICORD is available for non-commercial use (and further enrichment) by the research and education communities which may include development of educational resources for COVID-19, use of RICORD to create AI systems for diagnosis and quantification, benchmarking performance for existing solutions, exploration of distributed/federated learning, further annotation or data augmentation efforts, and evaluation of the examinations for disease entities beyond COVID-19 pneumonia. Deliberate consideration of the detailed annotation schema, demographics, and other included meta-data will be critical when generating cohorts with RICORD, particularly as more public COVID-19 imaging datasets are made available via complementary and parallel efforts. It is important to emphasize that there are limitations to the clinical “ground truth” as the SARS-CoV-2 RT-PCR tests have widely documented limitations and are subject to both false-negative and false-positive results which impact the distribution of the included imaging data, and may have led to an unknown epidemiologic distortion of patients based on the inclusion criteria. These limitations notwithstanding, RICORD has achieved the stated objectives for data complexity, heterogeneity, and high-quality expert annotations as a comprehensive COVID-19 thoracic imaging data resource.

This statistic depicts the annual compensation among radiologists in the U.S. according to different sources (organizations), as of 2018. According to Integrated Healthcare Strategies, annual salaries for radiologists averaged some *** thousand U.S. dollars.

Graph and download economic data for Hourly Compensation for Health Care and Social Assistance: Diagnostic Imaging Centers (NAICS 621512) in the United States (IPURN621512U120000000) from 1994 to 2024 about diagnostic imaging, healthcare, social assistance, compensation, health, NAICS, IP, hours, and USA.

Number of Businesses statistics on the Diagnostic Imaging Centers industry in the US

Access databases and original data files of radiology and digital imaging procedures undertaken nationally

RadGraph is a dataset of entities and relations in radiology reports based on our novel information extraction schema, consisting of 600 reports with 30K radiologist annotations and 221K reports with 10.5M automatically generated annotations.

We release a development dataset, which contains board-certified radiologist annotations for 500 radiology reports from the MIMIC-CXR dataset (14,579 entities and 10,889 relations), and a test dataset, which contains two independent sets of board-certified radiologist annotations for 100 radiology reports split equally across the MIMIC-CXR and CheXpert datasets. We also release an inference dataset, which contains automatically generated annotations for 220,763 MIMIC-CXR reports (around 6 million entities and 4 million relations) and 500 CheXpert reports (13,783 entities and 9,908 relations) with mappings to associated chest radiographs.

Financial overview and grant giving statistics of American Association For Women In Radiology

Brand performance data collected from AI search platforms for the query "AI in radiology accuracy statistics".

This dataset contains the results of an online survey run in summer of 2017 on the research data management (RDM) practices and perceptions of researchers using magnetic resonance imaging (MRI) to study human neuroscience (N=144). The dataset includes responses to multiple choice questions ordered roughly according the phases of a typical research project including data collection, analysis, and sharing. It focuses on a range of RDM topics, including the type of data collected, software and tools used to analyze and manage data, and the degree to which data management practices are standardized within a research group. It also includes participant ratings on the maturity of their data management practices and those of the field at large on a 1-5 scale from ad hoc to refined and responses about perceptions of new scholarly communications practices including data sharing, data reuse, and Open Access publishing.The survey instrument used can be found at the link in the reference below.

Graph and download economic data for Output per Worker for Health Care and Social Assistance: Diagnostic Imaging Centers (NAICS 621512) in the United States (IPURN621512W001000000) from 1995 to 2022 about diagnostic imaging, healthcare, social assistance, output, health, NAICS, IP, employment, and USA.

This statistic displays the annual rate of radiographers and radiologists working in England from 2010/11 to 2017/18, per 10,000 MRI and CT scans. In 2010/11, there were **** radiographers per 10,000 diagnostic scans, by 2017/18 this rate had dropped to ***.

Graph and download economic data for Producer Price Index by Industry: Diagnostic Imaging Centers: Diagnostic Imaging Services (PCU6215126215124) from Jun 1994 to May 2025 about diagnostic labs, services, PPI, industry, inflation, price index, indexes, price, and USA.

The Global Radiology Market Size Was Worth USD 76.42 Billion in 2022 and Is Expected To Reach USD 300.51 Billion by 2030, CAGR of 18.76%.

According to a survey of radiologists in North America in 2020, almost ** percent indicated their institution did not have 3D printing. Around a quarter of radiologists did have 3D printing at their institution but it was only used for research.

Snapshot img

The Radiology Market study is a comprehensive report with in-depth qualitative and quantitative research evaluating the current scenario and analyzing the growth of USD 17133.69 million and CAGR of 6.31% by segment Product and Geography during the forecast period 2020 to 2025

Furthermore, this report extensively covers market segmentation by product (X-ray, ultrasound, computed tomography, and others) and geography (North America, Europe, Asia, and ROW). The market report also offers information on several market vendors, including Agfa-Gevaert NV, Canon Inc., Esaote SpA, FUJIFILM Holdings Corp., General Electric Co., Koninklijke Philips NV, Samsung Electronics Co. Ltd., Shenzhen Mindray Bio-Medical Electronics Co. Ltd., Shimadzu Corp., and Siemens AG

Download the Report Sample to Unlock the Smart Room Heater Market Size for the Forecast Period and Other Important Statistics

Parent Market Analysis

Technavio categorizes the Radiology Market as a part of the Health Care industry within the Health Care Equipment and Supplies industry. Our Technavio research report has extensively covered external factors influencing the parent market growth potential in the coming years, which will determine the levels of growth of the forecast year.

Radiology Market: Key Drivers, Trends, and Challenges

Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic's impact on the radiology industry. The holistic analysis of the drivers will help deduce end goals and refine marketing strategies to gain a competitive edge.

Key Radiology Market Driver

One of the key factors driving growth in the market is the increasing occurrences of chronic disorders among the older population. The risk of developing diseases increases proportionately with age. According to CDC, nearly 80% of the elderly in the US suffer from at least one chronic condition. In addition, the AMA estimates that at least 60% of individuals aged 65 years and above will be living with more than one chronic condition by 2030. This increase in the ageing population will drive the demand for improved healthcare facilities and advanced treatment options and medication. With the rapid growth in the geriatric population globally, the prevalence of age-associated diseases such as Alzheimer’s disease, Parkinson’s disease, arthritis, and dementia, along with cardiovascular diseases (CVDs) and cancer, is expected to increase. Thus, the rising number of chronic diseases across the world would further drive growth in the global market during the forecast period.

Key Radiology Market Challenge

The lack of early diagnosis will be a major challenge for the market during the forecast period. Early diagnosis of any disease focuses on detecting symptomatic patients as early as possible, so they have the best chance for successful treatment. For example, when cancer care is delayed or inaccessible, there is a lower chance of survival of the patient, or it leads to greater problems associated with treatment and higher costs of care. The lack of awareness about the symptoms is an important barrier to the early diagnosis of several chronic diseases such as cancer. Early diagnosis improves the outcomes by providing care at the earliest possible stage and it, therefore, becomes an important public health strategy. However, the lack of early diagnosis of chronic diseases further restricts the growth of the market because, by the time the patient becomes aware of the disease, the need for radiology becomes obsolete.

Radiology Market Value Chain Analysis

Our report provides extensive information on the value chain analysis for the market, which vendors can leverage to gain a competitive advantage during the forecast period. The end-to-end understanding of the value chain is essential in profit margin optimization and evaluation of business strategies. The data available in our value chain analysis segment can help vendors drive costs and enhance customer services during the forecast period.

Who are the Major Radiology Market Vendors?

Agfa-Gevaert NV - Radiology: The company's Radiology products such as Dura-Line Flat Panel DR. The offset solutions segment focuses on the offset printing industry, offering commercial, newspaper and packaging printers and the most extensive range of integrated prepress and printing solutions. The digital print & chemicals segment focuses on sign and display printing with a range of highly productive and versatile wide-format inkjet printers with matched inks, powered by dedicated workflow software. Under the radiology solutions segment, the company focuses on a wide range of diagnostic imaging solutions, providing analogue and digital imaging technology to meet the needs of specialized clinicians in hospitals and imaging centres globally.

The report analyzes the market’s competitive landscape and offers informatio

Graph and download economic data for Sectoral Output for Health Care and Social Assistance: Diagnostic Imaging Centers (NAICS 621512) in the United States (IPURN621512T300000000) from 1994 to 2022 about diagnostic imaging, healthcare, social assistance, health, NAICS, IP, production, and USA.

Japanese company Hitachi accounted for three percent of the world's market for diagnostic imaging in 2017. By 2024, this share is expected to decrease to 2.7 percent. Diagnostic imaging allows medical examiners to observe the inside of a body to establish a medical condition. Different techniques and machines allow radiologists and other health professionals to take a picture of the structures and activities occurring in the body. The best-known types of diagnostic imaging are radiography (X-rays), ultrasound, computed tomography (CT), and magnet resonance imaging (MRI). The global top 3 companies The global diagnostic imaging market is dominated by three companies which are all expected to maintain a share of about 20 or more percent until 2024. These three companies are German Siemens (Healthineers), U.S.-based General Electric Healthcare, and Philips from the Netherlands. The total global diagnostic imaging market currently is estimated at around 40 billion U.S. dollars. One of the main drivers for the market is the growing demand for early stage diagnoses of chronic diseases of an increasingly aging population, especially in developed countries. The importance of medical imaging Today, medical diagnosis without diagnostic imaging is hardly imaginable. It makes it possible to take a detailed image of the human body and his structures, thus allowing an exact diagnosis and to choose the most appropriate treatment. Although most types of diagnostic imaging are painless, some require a patient to remain still for an extended period inside a machine, which causes problems for some patients, i.e. claustrophobia. Other methods could involve exposure to some radiation or being anesthetized. The fact that there are, for example, annually 35-40 million MRI scans in the United States alone, shows the massive impact and importance of medical imaging in today’s health care.

RadGraph is a dataset of entities and relations in full-text radiology reports. We designed a novel information extraction (IE) schema to structure clinical information in a radiology report with four entities and three relations. Our train set consists of 500 MIMIC-CXR radiology reports annotated according to our schema by board-certified radiologists. Our test set consists of 50 MIMIC-CXR and 50 CheXpert reports, which are independently annotated by two board-certified radiologists. Additionally, we release annotations generated by a benchmark deep learning model that achieves a micro F1 of 0.82 (MIMIC-CXR test set) and 0.73 (CheXpert test set) on an evaluation metric for end-to-end relation extraction, where entity boundaries, entity types, and relation type must be correct. We use our model to automatically generate entity and relation labels across 220,763 MIMIC-CXR reports and 500 CheXpert reports, where annotations can be mapped to associated chest radiographs in the MIMIC-CXR and CheXpert datasets respectively. The dataset, which includes reports, entities, and relations, is de-identified according to the US Health Insurance Portability Act (HIPAA). This dataset is intended to support the development of natural language processing (NLP) methods for entity and relation extraction in radiology as well as enable multi-modal use cases that can leverage entities, relations, and associated radiographs.

This project aims to create an anonymized data set of COVID-19 cases with a focus on radiological imaging. This includes images with extensive metadata, such as admission-, ICU-, laboratory-, and patient master-data.

This repository contains image data from the Institute for Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany.