I am happy to announce this web application, designed to assist researchers working in pump-probe and time-resolved photoluminescence microscopy. This tool aims to make estimating the Contrast-to-Noise Ratio (CNR) for noisy 1-dimensional Gaussian profiles as simple and efficient as possible. It’s completely free to use.
Why estimate CNR?
Contrast-to-noise ratio (CNR) is a necessary metric in fields like pump-probe and time-resolved photoluminescence microscopy. It helps to understand the quality of your signal amidst the noise, providing insights into the accuracy and precision of your diffusion measurements. While designed with these applications in mind, the tool may also be useful for other purposes where CNR estimation is needed.
What it does
The CNR Estimator is designed with user-friendliness in mind. Here’s what you can expect:
- Easy Data Input: Enter your data as a list of comma-separated or space-separated values.
- Accurate Estimations: The app utilizes a robust algorithm to provide accurate CNR estimates based on your input data.
- Under the hood: I provide a detailed explanation of the estimation algorithm, ensuring you understand how the result is derived. You could even take this information to build your own script in another language using the information given.
- Instant Results: Get your CNR estimate within seconds.
How to use
- Prepare Your Data: Before using the tool, make sure to subtract your background (baseline) and normalize your data so the peak height is set to unity.
- Enter Your Data: Paste your noisy Gaussian profile as a list of comma-separated or space-separated values into the input field.
- Get Your Estimate: Click on the “Calculate CNR estimate” button to receive your CNR estimate instantly.
Get Involved
I am passionate about fostering a collaborative environment. Check out the open-source code for the full DICE application on GitHub. Your contributions and feedback are highly valued and will help improve the app further.
Citations
- Zenodo Archive: Joseph J. Thiebes. (2023). thiebes/DICE. Zenodo. https://doi.org/10.5281/zenodo.10258191
- Research Paper: Joseph J. Thiebes, Erik M. Grumstrup; Quantifying noise effects in optical measures of excited state transport. J. Chem. Phys. 28 March 2024; 160 (12): 124201. https://doi.org/10.1063/5.0190347
Contact Me
If you have any questions, suggestions, or feedback, please don’t hesitate to let me know. Your input is crucial in helping me make this tool even better.
Happy Estimating!
Joseph J. Thiebes, Ph.D. 