Calantric™ Digital Solutions reportedly offers artificial intelligence (AI)-powered apps, bolsters lesion detection, facilitates triage priorities and enhances workflow efficiency.
Could a new cloud-based suite of imaging apps help radiologists navigate increasing imaging volume in their practices?
Calantric Digital Solutions offer apps that target three key aspects of radiology workflow, according to Bayer, the manufacturer of the new platform. The company said the system includes apps to assist with lesion detection, triage of suspicious findings for expedited review, and automation of routine tasks and measurements.
The artificial intelligence (AI)-powered aspects of the imaging app platform and access to digital tools may be beneficial in improving diagnostic accuracy and efficiency with imaging assessment, according to Ryan K. Lee, MD, MBA, MRMD, chair of the department of radiology with Einstein Healthcare Network in Philadelphia
“AI has the potential to transform health care, and, particularly in medical imaging, it can turn the growing amounts of data into value-adding insights to support radiologists and their teams in their decision-making,” noted Dr. Lee, an associate professor at the Sydney Kimmel College at Thomas Jefferson University.
Offering a variety of applications, ranging from assistance with pulmonary nodule detection to triage of suspected intracerebral hemorrhage, the initial platform for Calantric Digital Solutions is primarily focused on the assessment of thoracic and neurological diseases, according to Bayer. However, the company said it plans to add more disease-specific apps to the platform in the future.
MRI or Ultrasound for Evaluating Pelvic Endometriosis?: Seven Takeaways from a New Literature Review
September 13th 2024While noting the strength of MRI for complete staging of disease and ultrasound’s ability to provide local disease characterization, the authors of a new literature review suggest the two modalities offer comparable results for diagnosing pelvic endometriosis.
Can Radiomics and Autoencoders Enhance Real-Time Ultrasound Detection of Breast Cancer?
September 10th 2024Developed with breast ultrasound data from nearly 1,200 women, a model with mixed radiomic and autoencoder features had a 90 percent AUC for diagnosing breast cancer, according to new research.