- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Canon's Cartesion Prime is a Digital PET/CT Solution Fit for the Times
Canon's latest entry into the PET/CT market is a digital, air-cooled system that provides customizable solutions for a range of clients.
As the country--and the world--continues to grapple with the ongoing COVID pandemic, the imaging industry is looking to re-find its footing in an evolving landscape where customized solutions are key to success.
Enter Canon Medical's Cartesion Prime digital PET/CT, introduced in 2019, which provides a high-performance, adaptable system for today's evolving imaging technology. Optimizing both workflow and image quality via advanced silicon photomultiplier design with one-to-one coupling, fast time-of-flight and deep learning reconstruction technology, “this advanced technology has led to image quality improvements, while optimizing dose efficiency to reduce patient risk and speeding up acquisition time for improved throughput," said Tim Nicholson, managing director, Molecular Imaging Business Unit, Canon Medical Systems USA.
In an interview with Diagnostic Imaging, Nicholson expanded on the needs of the industry and how Canon is answering the call.
FDA Approves Fluorescence Imaging System for Detecting Residual Breast Cancer
April 18th 2024The combination of the optical imaging agent Lumisight and the fluorescence imaging device Lumicell Direct Visualization System, collectively known as LumiSystem, reportedly offers 84 percent accuracy with real-time detection of residual breast cancer after lumpectomy procedures.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
April 11th 2024The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.
