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Global Digital X-Ray Sector Forecast to Reach USD 10.46 Billion by 2020

By MedImaging International staff writers
Posted on 21 Feb 2016
A new market research report provides an overview of the digital X-ray market, and includes forecasts of revenue and market share through 2020.

The report investigates market trends, drivers, restraints, challenges, opportunities, and strategies, and analyses the digital X-Ray market by application, technology, and portability according to the type of system, end user, price, and region.

The Digital X-Ray "Global Forecast to 2020” was published by MarketsandMarkets (Dallas, TX, USA). The researchers conclude that the market is expected to grow at a Compound Annual Growth Rate (CAGR) of 11.2% and reach USD 10.46 Billion by the year 2020. In 2015 the market stood at USD 6.15 Billion.

The researchers expect the general radiography segment, for example chest imaging, orthopedics, and cardiovascular applications to make up the largest share of the market. The growth of the chest imaging segment is related to an increase in the incidence of lung diseases. The researchers also conclude that fixed Digital X-Ray systems are expected to account for the largest share of the global market in 2015, due to increasing government spending on advanced diagnostic equipment. Most of the systems were installed in diagnostic centers in 2015. The market report looks at trends in new digital X-ray systems, retrofit and refurbished systems, price categories, and regions. The North American market is expected to account for most of the market during through 2020.

Principals in the Digital X-Ray market include Canon (Tokyo, Japan), Carestream (Rochester, NY, USA), Fujifilm Medical Systems (Tokyo, Japan), GE Healthcare (Chalfont St Giles, Buckinghamshire, UK), Hitachi Medical (Tokyo, Japan), Hologic (Bedford, MA, USA), Royal Philips (Amsterdam, the Netherlands), Shimadzu (Kyoto, Japan), Siemens Healthcare (Erlangen, Germany), and Toshiba Medical Systems (Otawara, Tochigi Prefecture, Japan).

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Image: Researchers develop a vision-language model trained on large-scale data to generate clinically relevant findings from chest computed tomography images through visual question answering (Ms. Maiko Nagao from Meijo University, Japan)

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