Volocity® Quantitation offers an extensive array of features for the in-depth analysis of structure and function in 2D, 3D, and 4D. Unlock the potential to conduct morphological analysis, measure fluorescence localization and colocalization, and explore trends within your data.

Effortlessly present and publish your findings with measurement overlays, tables, statistical data, charts, and tracks, creating a comprehensive representation of your results.

This powerful analysis tool supports various applications, including FRAP (Fluorescence Recovery After Photobleaching), FRET (Fluorescence Resonance Energy Transfer), colocalization, and ratiometric analysis, enabling you to delve deeper into your research and draw meaningful conclusions from your data.

See your cells with stunning clarity

• Enhance your image data by eliminating out-of-focus information, a result of the optical properties of the microscope, from standard widefield fluorescence images. This process produces exceptional confocal-quality images, enabling precise measurements from the enhanced data.

• Experience convenience and speed with batch processing, which allows you to efficiently handle multiple data sets simultaneously.

• Optimize processing speed and memory usage by breaking the image into blocks, ensuring faster and less memory-intensive operations.

• Achieve even higher image quality for data acquired on your imaging system with this advanced tool, providing further improvements to enhance the clarity and detail of your research images.

Tailor to your research

• Tailor the process to your specific imaging system by selecting from a variety of Point Spread Functions (PSFs) - you can either calculate PSFs for widefield, confocal, two-photon confocal, spinning disk, point scanning confocal imaging systems, or even measure a PSF from your own setup to acquire data.

• Benefit from the award-winning Iterative Restoration algorithm, developed by Quorum Technologies, which is based on published Maximum Entropy techniques. This advanced algorithm is designed to make significant improvements in resolution both in the XY plane and Z-axis, enhancing the quality of your images.

• Experience the power of the Fast Restoration algorithm, also developed by Quorum Technologies. This algorithm rapidly computes and produces superior results when viewed in the XY plane. It utilizes every voxel in the volume during a single-pass process, leading to enhanced visual quality and precise outcomes.

• To further accelerate image restoration and other processing-intensive tasks, you can utilize the Imaging Computer Server, optimizing the performance of Volocity and expediting data processing. This feature ensures that you can efficiently handle large datasets and complex analyses for a seamless research experience.

RestorationMV

Volocity® RestorationMV seamlessly integrates the high-speed deconvolution algorithms from Microvolution, enhancing the quality and resolution of 3D datasets with ease. When applied to standard widefield fluorescence microscope images, the outcome is remarkable, delivering superior quality confocal data. The use of Volocity Restoration on confocal, spinning disk, and multi-photon images can further unveil intricate details by effectively eliminating out-of-focus haze. This indispensable imaging tool accommodates a wide array of file formats from both confocal microscopes and widefield systems, making it a versatile and valuable asset for your research needs.

Restorationmv hardware acceleration

RestorationMV is an image restoration algorithm that enhances the quality of images obtained from various microscopy techniques by reducing noise, improving resolution, and enhancing details. To achieve these results, the restorationMV module relies heavily on the computational capabilities of the video card (GPU) in your computer.

The need for a fast discrete video card with a significant amount of VRAM (Video Random Access Memory) is due to the intensive computational requirements of image restoration algorithms. Here's why:

1. Parallel Processing: Image restoration algorithms, especially those used in Volocity, involve complex mathematical operations that can be performed in parallel. GPUs are designed to excel at parallel processing, with thousands of cores that can handle multiple tasks simultaneously. This enables them to accelerate image processing tasks significantly compared to CPUs (Central Processing Units), which are more suited for sequential processing.

2. High Memory Bandwidth: Image restoration involves processing large datasets, and the data needs to be moved quickly between the GPU's memory and the processor. GPUs typically have higher memory bandwidth compared to CPUs, allowing them to efficiently handle the large data sets involved in image restoration. This is particularly important when dealing with high-resolution images or large image stacks acquired over time.

3. Large VRAM Capacity: Image restoration algorithms often require the storage of intermediate results and temporary data, especially during complex iterative processes. Having sufficient VRAM ensures that the GPU can store all the necessary data without needing to constantly transfer data between the GPU and the system's RAM. This reduces the processing overhead and speeds up the restoration process.

4. Complex Algorithms: RestorationMV utilizes advanced deconvolution techniques, which are computationally intensive. These techniques aim to reverse the blurring effects caused by the imaging process and enhance the final image's clarity and resolution. To handle these complex algorithms efficiently, a powerful GPU with ample VRAM is crucial.

For Volocity's restorationMV module, having a GPU with at least 4GB of VRAM ensures that the module can run effectively for a wide range of image sizes and complexities. However, for larger datasets or more computationally challenging scenarios, GPUs with 6GB or more of VRAM, such as the RTX 2070, 3070, 4070, or Quadro RTX A4000 and A4500 would be preferred as they can handle the workload more efficiently, reducing processing times and allowing for smoother interactions with the software.