Article Body Display Box - Home page (QR Code for mobile)

Aug 2, 2011
2011 08 03 14 43 26 740 Url M Auntminnieeurope Com 150

2011 08 03 14 43 26 740 Url M Auntminnieeurope Com 150
Familiar with QR codes? Scan this graphic using the camera on your mobile phone and you'll be instantly connected to AuntMinnieEurope Mobile.

Latest in Imaging Informatics
Low-quality axial T2-weighted MRI scans with gradient-weighted class activation mapping. The low-quality MRI scans (top row) show blurred structures and artifacts making zonal and capsule boundaries indistinguishable. On the same scans with gradient-weighted class activation map overlays (bottom row), red indicates regions that were most heavily weighted by the deep learning model toward the low-quality prediction.
AI framework could improve MRI quality control in prostate cancer
August 19, 2026
Nanox Logo 4
Nanox AI signs UK distribution deal for HealthOST bone health software
August 18, 2026
Pexels Cottonbro 5867701 (1)
Review highlights opportunities and risks of AI in pediatric imaging
August 17, 2026
Shutterstock 1918864388
AI performs well in breast screening, but density complicates the picture
August 13, 2026
Related Stories
2011 05 24 11 21 33 746 Cyber Informatics 70
Imaging Informatics
Can radiologists really trust PACS salespeople?
2011 07 01 10 02 13 643 Ziv Rosenbaum Thumb
Clinical News
10 golden rules for PACS implementation: Tips from Israel
2011 06 30 16 31 48 449 Arnon Makori 70
Imaging Informatics
Enterprise-wide PACS enhances patient management in Israel
2011 06 27 09 36 40 776 Sectra Mammography Unit Thumb
Clinical News
Sectra to sell mammography business to Philips
More in Imaging Informatics
AI framework could improve MRI quality control in prostate cancer
By Amerigo Allegretto
The framework uses a DL model trained on low- and high-quality MR images and helped improve radiologist accuracy.
August 19, 2026
Low-quality axial T2-weighted MRI scans with gradient-weighted class activation mapping. The low-quality MRI scans (top row) show blurred structures and artifacts making zonal and capsule boundaries indistinguishable. On the same scans with gradient-weighted class activation map overlays (bottom row), red indicates regions that were most heavily weighted by the deep learning model toward the low-quality prediction.
Nanox AI signs UK distribution deal for HealthOST bone health software
By AuntMinnieEurope.com staff writers
HealthOST analyzes routine CT scans for spine assessment.
August 18, 2026
Nanox Logo 4
Review highlights opportunities and risks of AI in pediatric imaging
By Claudia Tschabuschnig
Adult-trained AI tools may underperform in children, requiring pediatric-specific datasets, age-stratified validation, and stronger clinical oversight for safe deployment, researchers say.
August 17, 2026
Pexels Cottonbro 5867701 (1)
AI performs well in breast screening, but density complicates the picture
By Claudia Tschabuschnig
While AI can support breast cancer risk assessment, its performance declined as breast density increased, while variations related to equipment vendor and measurement level may complicate personalized screening.
August 13, 2026
Shutterstock 1918864388
Azra AI, Blackford form imaging, care navigation partnership
By AuntMinnie.com staff writers
The companies aim to ensure patients identified through imaging are promptly reached and managed through the appropriate care pathway.
August 5, 2026
Ai Handshake
Median Technologies signs Canon Medical partnership for eyonis LCS
By AuntMinnie.com staff writers
Canon's subsidiary Olea Medical will leverage its CT imaging platform to support distribution of Median's software.
July 30, 2026
Business Handshake Intelligence 400 (1)
EU AI Act brings radiology AI oversight into daily practice
By Claudia Tschabuschnig
A new opinion paper calls on European imaging departments to strengthen AI auditing and monitoring in patient care.
July 21, 2026
The European Parliament in Brussels approved the EU AI Act in 2024, establishing a risk-based regulatory framework for artificial intelligence, including high-risk medical AI systems.
Radiologists can identify three out of four AI-generated images
By Amerigo Allegretto
Radiologists found it particularly difficult to distinguish between real and AI-generated CT and MR images.
July 17, 2026
Top eight incorrectly classified synthetic images (Most convincing fake images). Images A, B, C, D, E, F, G and H were the most infrequently correctly classified images at 24%, 43%, 59%, 64%, 69%, 71%, 71% and 73% respectively. All images are AI-generated. Images A, B and C are head CTs. Images D and E are chest CTs. Image F is a cardiac CT. Image G is a musculoskeletal MRI. Image H is a head MRI. Images are republished under a Creative Commons license (CC BY 4.0).
Incorrect AI suggestions influence reader performance on mammography
By Amerigo Allegretto
The biggest impact on reader performance stemmed from false-negative AI suggestions.
July 14, 2026
A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.
The cost of AI, and finding its breakeven point
By Claudia Tschabuschnig
Who pays, what, where, and when: speakers at the Royal College of Radiologists' Global AI Conference dug into what AI actually costs and when, if ever, it pays for itself.
July 9, 2026
Who's paying, and for what, is the question that actually decides whether AI in healthcare gets funded.
AI aims to decode targeted radiotherapy response
By Claudia Tschabuschnig
Same administered activity, different results. Speakers at the Royal College of Radiologists’ 2nd Annual Global AI Conference argued AI could help move targeted radionuclide therapy beyond a one-size-fits-all approach toward more precise, personalized treatment.
July 8, 2026
Experts at the Royal College of Radiologists’ 2nd Annual Global AI Conference discussed how AI could help move cancer care toward more personalized treatment, from targeted radionuclide therapy dosing to drug discovery.
RCR: Agentic AI is off the leash, and already a workhorse for health systems
By Claudia Tschabuschnig
The technical crowd took the stage at the 2nd Annual Global AI Conference in London last week, to show radiologists where agentic AI is running, how it operates across a spread of autonomy, and why only the highest tiers demand serious governance.
July 7, 2026
Dr. Rowland Illing, chief medical officer at Amazon Web Services (AWS) and a former interventional radiologist.
Page 1 of 418
Next Page