10 Mar AI uses optical aberration for better microscopy
A team of researchers is proposing to make use of chromatic aberration – an optical phenomenon that usually reduces image quality – to produce high-quality images with standard microscopes. The new method is used in quantitative phase microscopy (QPI), a type of microscopy widely used to examine cells. According to the researchers, the first biomedical QPI applications already exist. However, both imaging speed and quality still need to be optimized in order for QPI to achieve a breakthrough in medicine, explain the scientists from the Görlitz Center for Advanced Systems Understanding (Casus) at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and from Imperial College and University College London, who are working together to improve QPI.
QPI – Efficient but expensive
Stained or otherwise labeled biological samples provide valuable information. However, the disadvantage for a broad application in clinical diagnostics is that the procedure is time-consuming and requires expensive equipment and consumables. For this reason, research in recent years has increasingly focused on label-free microscopy methods such as QPI. Here, it is not only the amount of light absorbed or scattered by the sample that is of interest. Using the scattering information, QPI also records how the sample shifts the phase of the light passing through it – a change that is directly related to its thickness, refractive index and other structural properties. QPI also requires quite expensive equipment, unlike computerized QPI.
The alternative: computational QPI
One of the best known computational QPI approaches is based on the solution of the intensity transport equation (TIE). This differential equation allows the calculation of an image of the sample based on the recorded phase changes. The approach can be easily integrated into existing optical microscopy systems and provides high quality images. However, the TIE method often requires multiple exposures with different focus distances to eliminate artifacts. However, working with focus stacks is time-consuming and technically demanding, so this type of TIE-based QPI is often not practical in a clinical setting.
Chromatic aberration: image error becomes tool
“Our approach is based on similar principles as the TIE, but only requires a single image due to a clever combination of physical knowledge and generative AI,” explains Professor Artur Yakimovich, head of a Casus junior research group. The information about the phase shift caused by the biological sample does not come from additional images with different focus distances. Instead, chromatic aberration can be used to generate a focus stack from a single image. Most microscope lens systems cannot perfectly focus the wavelengths of (polychromatic) white light to a single convergence point – a disadvantage that only highly specialized lenses can compensate for. This means, for example, that red, green and blue (RGB) light have slightly different focus distances. “By detecting the phase shifts of these three wavelengths separately with a standard RGB detector, we can create a continuous focus stack that enables computer-aided QPI,” explains Yakimovich. “So we turn the disadvantage into an advantage.”
AI leads to breakthrough
Gabriel della Maggiora, PhD student at Casus, adds: “A major challenge has to be solved if you want to make chromatic aberrations usable for QPI: the focus distance between red and blue light is very small.” The standard TIE solution does not deliver meaningful results in this case. “Then we came up with the idea of using artificial intelligence. This idea proved to be decisive.” Maggiora explains: “After training a generative AI model with a freely available dataset of 1.2 million images, it was able to determine the phase information despite the very limited data input.”
Testing on clinical samples
According to the team, they used a generative AI model for image enhancement that they had presented last spring: the Conditional Variational Diffusion Model (CVDM). With this model, they were able to realize computational QPI based on chromatic aberrations. For example, they validated their generative AI-based approach using a conventional brightfield microscope equipped with a commercially available color camera to capture microscopic images of real clinical samples. When analyzing red blood cells in a sample of human urine, the method was able to visualize the characteristic donut-shaped structure of these cells – a result that another established computational TIE-based method could not deliver, report the scientists. An additional advantage was the almost complete absence of cloud artifacts in the images calculated with the new QPI method.
Original publication:
[G. della Maggiora, L. A. Croquevielle, H. Horsley, T. Heinis, A. Yakimovich, Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models, presented at the 39th Annual Conference on Artificial Intelligence by the Association for the Advancement of Artificial Intelligence (AAAI) and accepted for publication in the Proceedings of the 39th AAAI Conference on Artificial Intelligence, preprint available: https://arxiv.org/abs/2406.04388]
Source: www.hzdr.de
Image: Blaurock/Casus
