Modular software for scientific image reconstruction

Modular software for scientific image reconstruction

Technology News |
By Wisse Hettinga

EPFL engineers have developed new software called Pyxu that makes it easier and faster to reconstruct images taken at any scale.

Their system employs reusable, and universally applicable, bricks of algorithms

Scientists use an array of imaging instruments to look inside living organisms, sometimes as they move, and to observe inert objects without altering their state. Such instruments include telescopes, microscopes, CT scanners and more. But these instruments, even when working at maximum capacity, often generate only partial images or images of too low quality to provide much insight. That’s where powerful algorithms come in – they can piece together bits of missing information, improve an image’s resolution and contrast, and flesh out sketchy objects. Impressive advances have been made recently in this technique, known as computational imaging, to the point where it now plays a central role in many types of research.

Engineers working in a variety of fields have developed powerful algorithmic programs for this technique, yet each one is designed for a highly specific application, even though the underlying imaging physics is generally the same. That means scientists wanting to combine imaging methods must make a considerable effort to adapt different programs and get them to communicate. “We felt like we were always rewriting the same bits of code in order to adapt the programs we wanted to use,” says Sepand Kashani, a PhD student at EPFL’s Audiovisual Communications Laboratory (LCAV). So he teamed up with Matthieu Simeoni and Joan Rué Queralt, the former and current head of the Hub for Image Reconstruction at EPFL’s Center for Imaging, to develop application-agnostic algorithms to be shared across different fields. Today that software – called Pyxu – is available in open source.

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