Have you ever seen microscopic images so detailed that you can pick out single molecules? Behind those jaw-dropping pictures lies a crucial concept called the point spread function (PSF). Simply put, the PSF tells us how a single point of light—like an individual molecule—appears in the final microscope image. Accurately knowing the PSF helps scientists refine their images and push the limits of what optical microscopes can see.
However, every microscope is set up a little differently, which makes figuring out the right PSF tricky. Researchers often rely on simplified mathematical approximations, but these might not capture everything going on inside the microscope’s lenses and layers. So how can you tell if the PSF model you’re using is truly a good match for your microscope?
In our new paper, we tackle that challenge by developing a rigorous method to check how well a candidate PSF actually fits real microscope data. Here’s the gist of how it works:
- Measure & Model: We start by taking images of very small “point” objects (like tiny fluorescent beads or gold nanorods) under the microscope.
- Compare: We compute what those images ought to look like if our chosen PSF model were correct.
- Confidence Check: We then use a “confidence interval” approach to see if the actual pixels match what the math predicts, despite normal measurement noise and random fluctuations. The more pixels that fall within our predicted range, the better the PSF model fits.
This validation step might sound like a small detail, but it’s crucial for high-end microscopy. If the PSF is off, you could be misinterpreting the shapes or positions of microscopic features—like single molecules in fluorescence imaging. By systematically comparing various PSF options, researchers can find the one that truly matches their experimental setup, leading to sharper, more accurate images.
Our study demonstrates this validation with multiple types of microscopes, including both fluorescent (label-based) and label-free (coherent) setups. We show that for complex systems—such as microscopes with multiple layers of lenses and substrates—you really do need the “right” PSF model to capture everything correctly. Otherwise, you risk sacrificing clarity and precision in your results.
Ultimately, this new validation scheme provides a reliable tool for anyone working on cutting-edge microscopy. Whether you’re studying how molecules move inside cells or imaging tiny nanostructures on a chip, having confidence in your PSF is a game-changer. It ensures that the beautiful images you create reflect reality as closely as possible—letting you peer deeper into the microscopic world than ever before.
For more details, check out the full paper: https://ieeexplore.ieee.org/document/10857452
“Computational comparison and validation of point spread functions for optical microscopes” by Zicheng Liu, Yingying Qin, Jean-Claude Tinguely, and Krishna Agarwal.