Cardiovascular diseases cause one death every 33 seconds in America. Diagnosing these conditions, which account for approximately 20% of all deaths annually, can be difficult because the overlaying and natural fluorescence of cardiac tissue complicate diagnostic images.

A new algorithm described in Nature Cardiovascular Research could lead to clearer images, earlier diagnoses, and better outcomes.

"Enhancing visualisation of cardiac systems is just one application of this new tool," said Eric Lyons, a program director in the NSF Directorate for Biological Sciences. "This could also help advance live-cell imaging in other parts of the body, like the brain, and drive insights into fundamental biological processes and systems."

Current forms of imaging each have drawbacks, being limited by how broad or deep they can visualise, the ability to visualise small scales like molecules, the frame rate of cameras, and the speed of data acquisition and processing. The algorithm addresses many of these challenges and allows for simultaneous viewing of multiple parameters and measurement of the volume of heart chambers.

The tool uses an approach known as multiscale recursive decomposition, where images are broken down into smaller parts across multiple scales. This allows for the precise extraction of dynamic cardiovascular signals, which could enable physicians and researchers to diagnose cardiovascular disease earlier and more accurately. Better diagnoses are likely to lead to improved health outcomes.

The algorithm is fully compatible with commonly used microscopes, allowing for widespread use of the tool