Hologic, Inc.’s Company’s Chairman, President and Chief Executive Officer Steve MacMillan, joined a number of employees ...

Applying radiology and cardiology PACS ergonomics expertise to help pathologists avoid repetitive stress injuries that can arise from adopting digital pathology

A decades-long decline in the breast cancer death rate continues, but has begun to slow in recent years, while breast ...

The Aplio a-series from Canon Medical Systems is a new line of ultrasound systems delivering high performance for ...

At Agfa’s Radiological Society of North America’s (RSNA) 2019 booth, radiology professionals will discover intelligent ...

Celebrating its 10th Anniversary in 2019, Volpara Solutions remains committed to helping breast imaging centers achieve ...

Researchers from Intermountain Healthcare and Stanford University say 10 seconds is about how quickly a new system they studied that utilizes artificial intelligence (AI) took to accurately identify key findings in chest X-rays of patients in the emergency department suspected of having pneumonia.

Researchers at the University of Arizona Health Sciences are seeking a new and more accurate way to diagnose breast cancer and contribute to improved outcomes for patients worldwide.

For the first time, a sophisticated computer model has been shown to accurately predict two of the most challenging side effects associated with radiation therapy for head and neck cancer. This precision oncology approach has the potential to better identify patients who might benefit from early interventions that may help to prevent significant weight loss after treatment or reduce the need for feeding tube placement. Findings were presented at the 61st Annual Meeting of the American Society for Radiation Oncology (ASTRO), Sept. 15-18, 2019, in Chicago.