MAGNET extends Carestream pact

AuntMinnie.com staff writers
Mar 16, 2010

Carestream Health of Rochester, NY, will provide members of group purchasing organization MAGNET with its Carestream DRX-1 and Carestream DRX-Evolution systems, as well as Carestream RIS/PACS.

MAGNET already has an agreement with Carestream to purchase radiographic film, laser printers, computed radiography, digital radiography, and mammography computer-aided detection (CAD) systems.

Related Reading

Carestream passes mammo test, March 10, 2010

Carestream expands DRX-Evolution line, March 6, 2010

Carestream gets DR install for 2012 Olympics, February 25, 2010

Carestream hit with lawsuit over optical patents, February 25, 2010

Carestream takes RIS, PACS orders, February 17, 2010

Copyright © 2010 AuntMinnie.com

Latest in Digital X-Ray
Stroke Skull Xray 400
Can ChatGPT ‘data mine’ patient reports for stroke registries?
April 19, 2024
Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
AI proposed to help radiologists detect child abuse injuries
April 17, 2024
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
Related Stories
2009 03 25 14 14 33 939 Capitol Hill 70
Digital X-Ray
Medical groups tell Congress more radiation rules are needed
2010 02 17 16 01 45 740 Balter F4 Medium Thumbnail
Digital X-Ray
New paper updates guidelines on fluoro radiation injuries
2010 02 05 12 55 51 551 Auntminnie Brice Dual Energy Fig2c Thumb
Digital X-Ray
Virtual dual-energy DR improves lung lesion detection
2009 03 25 14 14 33 939 Capitol Hill 70
Digital X-Ray
Congress sets hearing to review medical radiation
More in Digital X-Ray
Can ChatGPT ‘data mine’ patient reports for stroke registries?
By Will Morton
ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.
April 19, 2024
Stroke Skull Xray 400
AI proposed to help radiologists detect child abuse injuries
By Will Morton
A team at Michigan State University has developed an AI model designed to detect rib fractures in children under 3 years old.
April 17, 2024
Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
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.
Page 1 of 373
Next Page