Microvolution® software delivers nearly instantaneous deconvolution by combining intelligent software programming with the power of a GPU
Developed by Stanford scientists, Microvolution software will improve your research:
- Work more effectively in dim light and realize greater success rates with live-cell and time-lapse experiments
- Create cleaner measurements after deconvolution (e.g., colocalization, FRET data, neurite lengths, fluorescence intensities)
- Make adjustments to your microscopy experiments on the fly and collect more data from the same sample
The software deconvolves images from widefield, confocal, two photon, light sheet, and HCA microscopes. Blind deconvolution option improves noisy data, such as deep tissue imaging. Multi-GPU options enable even giant images to be processed in seconds.
*Bruce MA, Butte MJ. Real-time GPU-based 3D Deconvolution, Optics Express, 2013; 21(4): 4766.
Speed
Deconvolve your fluorescence images, from small to very large, in a fraction of the time
Accuracy
Thin Filaments Are Preserved with Microvolution Software
Microvolution’s method starts with the proven Richardson-Lucy algorithm that is used by most software programs. Other vendors take mathematical shortcuts to speed up iterations, resulting in imprecise images after deconvolution. Microvolution takes no shortcuts. Our software delivers accurate images, up to 200 times faster.
Image courtesy of Molecular Devices.
Clarity
Increased resolution
When collected under the right conditions, deconvolution can help break the diffraction barrier. Pictured below are 180 nm separated lines on an Argo-SIM slide, imaged with widefield microscopy. Deconvolution brings a √2 improvement in visual resolution.
Image courtesy of Tong Zhang and Puifai Santisakultarm, Salk Institute.
Citations
Microvolution has been cited in the following publications
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