SVision LLC announces live cell image analysis software SVCell™ 1.0
Next generation, teachable microscopy image analysis software available for time-lapse analysis
SVision LLC, an emerging leader in the application of learning technologies for practical image recognition applications, today announced SVCell 1.0 version for live cell applications. The live cell module extends the capability of the ‘teachable’ SVCell software to address time-lapse microscopy applications. The software automatically detects and characterizes cells or subcellular objects in time-lapse images. It defines accurate boundaries for biological objects over time for dynamic spatial-temporal analysis, and also quantifies the kinetic gain or loss of fluorescence. It provides kinetic detection, measurements, and classifications within a powerful image and data analysis interface that links overlays, images, data charts and tables together in a single frame to facilitate data review and knowledge discovery.
SVCell 1.0 can be used for the quantitative characterization of dynamic events and phenotypes in time-lapse multi-channel fluorescence, phase contrast and brightfield images. The software is suitable for a broad range of applications including kinetics studies and label free applications such as cell morphology studies, proliferation and apoptosis assays, and cell culture observation including growth curve cell differentiation and phenotype analysis.
Two posters on SVision’s kinetic recognition technologies will be presented at the Experimental Biology Annual Meeting in Washington DC on May 2nd, and SVision staff will also be available at booth 1345 to discuss the program and the SVCell software. The posters can also be downloaded from the SVCell website at SVCell.com.
About SVision LLC
SVision develops and markets the next generation microscopy image analysis software, SVCell. SVCell enables scientists to create “recipes” for high performance image segmentation, optimized measurement and accurate pattern classification using a simple “teach by example” interface – guided by their biological knowledge rather than image processing expertise. The teaching is fast, easy and intuitive, and the taught recipe can be easily updated to match evolving experimental protocols. The validated recipe can then be executed in a high throughput imaging assay with fast, accurate and robust performance comparable to custom written algorithms or “turnkey” systems. SVision is a technological innovator with 27 issued and 19 pending US patents in high-speed image processing, pattern recognition, machine vision, automatic learning, spatial reasoning and data mining. Since 1999, SVision has been pioneering the use of learning technology in a broad range of practical image recognition applications. SVCell development is partially funded by the National Institute of Health (NIH) under multiple Small Business Innovative Research (SBIR) programs.