EOS 2017 sales up by 21%

AuntMinnie.com staff writers
Jan 16, 2018

Citing growth in Europe, the Middle East, and Africa (EMEA) and Asia-Pacific regions, orthopedic imaging technology developer EOS Imaging increased total worldwide sales by 21% in 2017.

Annual revenue was 37.1 million euros ($45.6 million U.S.), up 21% from revenue reported in 2016. The sales gain was primarily due to a 20% hike in equipment sales revenue in 2017 to 30 million euros ($36.9 million U.S.). The company sold 77 EOS digital radiography systems last year, compared with 60 scanners in 2016.

In 2017, total sales from the EMEA region increased 45% to 1.6 million euros ($20.4 million U.S.), while total sales from the Asia-Pacific region ballooned by 83% to 5.9 million euros (7.2 million U.S.), compared with 2016 results.

Latest in Digital X-Ray
Transgender Heart
Bone health appears normal in transgender youth on hormone therapy
April 5, 2024
Gavel3
Abortion care limitations raise medicolegal concerns in IR
April 3, 2024
(a) Raw example of a dynamic digital radiograph. (b) Contrast equalization using contrast-limited adaptive equalization shows improved anatomical visualization. (c) Training data is generated through manually labeling using SLEAP’s graphical user interface. (d-e) Neural network detection schematic. For each quadrant a series of two networks were used. The first identifies the quadrant center, the second using input of the first, then identifies individual anatomical landmarks within a quadrant. (d) Four neural networks were trained, each with the objective of identifying a chest quadrant centroid. The four separate quadrants are visualized as colored boxes (right upper quadrant, green; right lower quadrant, blue; left upper quadrant, red; left lower quadrant, yellow). (e) Serial centroid then anatomical identification. Two quadrant examples showing confidence maps of trained neural networks identifying quadrant centroids (left) and then anatomical confidence maps (right). Image and caption courtesy of Chest Pulmonary.
Can AI help chest DDR achieve clinical adoption?
April 1, 2024
Planet
Powering down idle IR systems can reduce environmental impact
March 21, 2024
Related Stories
2016 09 20 16 53 46 654 Heart Scan 400
Digital X-Ray
Doctors may be ordering too many coronary interventions
2017 12 22 18 57 6027 Yamada Tomo Cad 20171222181219
Digital X-Ray
CAD of chest tomosynthesis works best for new readers
2017 11 21 21 52 3424 Rsna 2017 400
Digital X-Ray
Fat distribution linked to heart attack risk
2017 11 15 23 12 3096 Hand X Ray 400
Digital X-Ray
Deep learning shows promise for bone age assessment
More in Digital X-Ray
Bone health appears normal in transgender youth on hormone therapy
By Will Morton
Bone mineral density is only slightly below the normal average among transgender youth undergoing gender-affirming hormone therapy.
April 5, 2024
Transgender Heart
Abortion care limitations raise medicolegal concerns in IR
By Will Morton
Interventional radiology (IR) specialists should be aware of shifting individual state laws on abortion so as to not be blindsided when called on to provide care to pregnant patients.
April 3, 2024
Gavel3
Can AI help chest DDR achieve clinical adoption?
By Will Morton
Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology.
April 1, 2024
(a) Raw example of a dynamic digital radiograph. (b) Contrast equalization using contrast-limited adaptive equalization shows improved anatomical visualization. (c) Training data is generated through manually labeling using SLEAP’s graphical user interface. (d-e) Neural network detection schematic. For each quadrant a series of two networks were used. The first identifies the quadrant center, the second using input of the first, then identifies individual anatomical landmarks within a quadrant. (d) Four neural networks were trained, each with the objective of identifying a chest quadrant centroid. The four separate quadrants are visualized as colored boxes (right upper quadrant, green; right lower quadrant, blue; left upper quadrant, red; left lower quadrant, yellow). (e) Serial centroid then anatomical identification. Two quadrant examples showing confidence maps of trained neural networks identifying quadrant centroids (left) and then anatomical confidence maps (right). Image and caption courtesy of Chest Pulmonary.
Powering down idle IR systems can reduce environmental impact
By Will Morton
Powering down idle interventional radiology (IR) imaging systems can substantially decrease carbon emissions and electricity costs.
March 21, 2024
Planet
Mercedes-Benz employs x-ray technology in crash tests
By Will Morton
Mercedes-Benz said it has performed the world's first crash with a real car using x-ray imaging technology.
March 21, 2024
An image illustrating the use of novel x-ray technology in crash tests.
Hysterectomies may be averted with UAE
By Will Morton
A minimally invasive treatment called uterine artery embolization (UAE) may be a promising alternative to hysterectomy in women due to severe bleeding after childbirth.
March 20, 2024
Uae
Training technique in AI helps preserve patient privacy
By Will Morton
The privacy of patient data in AI models trained on chest x-rays can be guaranteed – importantly, without significantly reducing the accuracy of models on large “real-world” data sets.
March 18, 2024
Ai Bias
AI flags rare humeral bone tumors on chest x-rays
By Will Morton
An AI algorithm can help identify rare tumors on upper arm bones in patients undergoing chest x-rays – findings not typically identified in daily reading practice.
March 13, 2024
The tumor localization/visualization results obtained by the proposed AI algorithm. Original chest x-ray images with a lesion (red circle = radiologists’ annotation of the lesion location) and AI's lesion localization result. These examples demonstrate that the proposed technique can successfully detect humeral tumors. Image and caption courtesy of Radiology: Artificial Intelligence.
Dark-field chest x-ray takes step forward
By Will Morton
German developers of dark-field chest x-ray appear to have overcome a technical limitation of the technology – namely, adjusting for photon scattering caused by interferometers used in the experimental system.
March 12, 2024
Chest X Ray
Study calls for continuous improvement of AI algorithms
By Will Morton
An external validation study conducted in a primary care clinic in Spain has demonstrated the value – as well as important limitations – of AI software for interpreting chest x-rays in clinical practice.
March 8, 2024
Image of patient (upper-left) in which, according to the radiologist's report, there is only consolidation, but the algorithm detects an abnormal rib (upper-right), consolidation (lower-left), and two nodules (lower-right). It is worth noting the confusion of a consolidation with mammary tissue and of two nodules with the two mammary areolae. Image courtesy of Scientific Reports.
Using deep learning with CT helps predict hip fractures
By Kate Madden Yee
A deep-learning model that includes digital x-rays reconstructed from 3D hip CT images shows promise for predicting subsequent fractures in patients with a relatively recent hip break, researchers have found.
January 31, 2024
Hip Joint
AI improves performance of nonradiologists in chest imaging
By Amerigo Allegretto
AI improves imaging interpretation by nonradiologist practitioners, which could aid in low-resource settings.
January 30, 2024
Chest X Ray Lateral View 400
Page 1 of 373
Next Page