Technology Enhances Quality of Deep Tissue Imaging
Researchers at the Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering developed a new approach for imaging through partially opaque, thick tissue and demonstrated its utility by capturing detailed images of weakly fluorescent neurons (nerve cells) covered by a thick layer of muscle tissue. This approach, known as "confocal wavefront shaping," has potential applications in non-invasive biological imaging of deep tissue in both research-oriented and clinical settings.
When light travels through biological tissue, it bounces off various structures, creating a scattered pattern that makes it impossible to form clear images. This is similar to how the light of car headlights scatter in heavy fog, making it difficult to see. The new technique, developed by doctoral student Dror Aizik, conducting the research under the guidance of Prof. Anat Levin, uses advanced optical and computational technology to "un-scatter" the light, allowing for crisp images of dim objects deep within thick tissue. The key innovations include corrections for both light entering the tissue and exiting it, based on iterative corrections and very straightforward assumptions. This dual correction approach allows for imaging using standard fluorescence microscopy techniques and relatively inexpensive light sources and detectors.
This initial version of the technique takes many minutes to complete the iterative determination of optimal corrections, posing some limitations on its used in present form. The team anticipates, however, that with improved hardware and refined algorithms, this process will be shortened significantly.
The study was published in Nature Communications on July 2, 2024.