Konica Minolta Unveils New PACS/RIS Platform for Radiologists
The Exa PACS/RIS platform reportedly combines AI-enabled worklist navigation tools with advances in multiplanar functionality and 3D-generated image segmentation.
Offering enhanced imaging capabilities as well as artificial intelligence (AI)-powered tools to promote radiology workflow efficiencies, Konica Minolta has launched the Exa PACS/RIS platform.
Key features of Exa PACS/RIS include the cloud-native NewVue feature, which utilizes AI to enhance efficient worklist navigation, and an automated tool from Clearpath Technologies that streamlines digital sharing of images and records with other providers, according to Konica Minolta.
Artificial-intelligence (AI) powered worklist navigation, improved multiplanar image reconstruction and streamlined sharing of images with other providers are some of the included feature with the newly launched Exa PACS/RIS platform. (Image courtesy of Konica Minolta.)
The company added that Exa PACS/RIS provides bolstered multiplanar reconstruction as well as 3D image reconstruction and segmentation, all of which can be viewed without clicking out of the Exa viewer.
“Confident diagnosis requires more than a single imaging study—it demands the right information, in the right place, at the right time. Our next-generation Exa PACS|RIS delivers powerful clinical and workflow tools, transforming data into actionable insights for smarter decision-making,” noted Matthew Andersen, the executive director of product management for Konica Minolta HCIT.
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
