Reliable, real-time selection of successfully reprogrammed iPS colonies can be made within seventy-two hours of their formation using time-lapse imaging and new kinetic image pattern recognition technology

BELLEVUE, WA – December 11, 2012  –  DRVision Technologies LLC, pioneer in teachable image recognition applications, has developed a new method for reliable, real-time selection of successfully reprogrammed induced pluripotent stem (iPS) cell colonies without the use of fluorescent reporters.  The method applies DRVision’s proprietary kinetic image pattern recognition technologies (patent pending) to image sequences of patient cells undergoing reprogramming to select iPS colonies as they first emerge. This method could shorten required reprogramming iPS colony selection time three fold. To commercialize the technology for broad deployment in stem cell research and production laboratories, DRVision is validating the method using a variety of protocols and cell types.

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It collaborates with Harvard’s Department of Stem Cell and Regenerative Biology and Nikon Corporation to develop tools and protocols for the image-guided reprogramming and differentiation of patient cells

BELLEVUE, WA – March 14, 2011 – DRVision Technologies LLC, pioneer in teachable image recognition applications, has received an up to $3.4 million grant from the National Heart, Lung, and Blood Institute (NHLBI) to develop advanced kinetic image pattern recognition (KIPR) tools.

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Next generation tool for scientists who need quantitative image analysis in their label-free, time-lapse imaging experiments.

DRVision Technologies LLC, a leader in the application of learning and recognition technologies for microscopy pattern analysis, today announced SVCell Phase Analyzer suite for comprehensive phase contrast image pattern analysis. The suite consists of the SVCell software and Phase Analyzer recipes for automated pattern analysis on applications such as cell proliferation, cell counting, wound healing and cell motility quantification from phase contrast movies.

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New time-lapse microscopy imaging systems and next generation fluorescent probes have enabled the visualization of rapid protein dynamics and molecular events. Quantitative characterization of these dynamic phenotypes could provide novel insights into disease formation and enable earlier and more effective interventions than those of traditional phenotypes using fixed and stained cells. Thus, there is a strong need for next generation high throughput tools that can be flexibly configured to accurately track and score dynamic characteristics at high volume in support of both basic (e.g. phenotyping) and applied research (e.g. drug discovery) in a broad range of subcellular applications.

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New company will expand collaboration with Nikon on software development

SVision LLC, an emerging leader in the use of advanced learning technologies for broad image recognition applications, announced today that it has established DRVision Technologies LLC (DRVision) to assume and continue the existing business of SVision LLC. DRVision has entered a comprehensive collaboration contract with Nikon Corporation. With this collaboration, the software technologies of both companies will be integrated to develop higher value-added products in Semiconductor Inspection Equipment, Systemized Microscopes and Live Cell Imaging solutions. To further the success of this collaboration, Nikon has made an equity investment in DRVision.

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Nikon selected SVCell as the analysis software for Nikon’s BioStation CT

SVision LLC, an emerging leader in the use of advanced learning technologies for broad image recognition applications, announced today that Nikon Corporation will begin distributing SVision’s SVCell™ together with Nikon’s BioStation CT, a fully integrated cell culture observation and monitoring system. For this purpose, SVCell will be sold under the Nikon brand using the name “CT Analysis Software SV”.

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Research grant will accelerate the application development and commercialization of teachable image recognition technologies for subcellular time-lapse assays

SVision LLC, an emerging leader in the application of learning technologies for practical image recognition applications, has received a Phase II Small Business Innovation Research (SBIR) Grant from the National Institute of Mental Health (NIMH) of the National Institutes of Health (NIH) to enhance the time-lapse, subcellular analysis capabilities for the company’s SVCell™ product.

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Innovative new technology supports next generation analysis software for broad imaging applications

SVision LLC, an emerging leader in learning technologies for image recognition applications, today announced that it has received notification of USPTO issuance for a key patent. This patent expands its intellectual property estate to 27 issued U.S. patents. The most recent patent 7,203,360 covers the Company’s next generation teachable object recognition innovation (called “soft matching”) that is incorporated into its microscopy image analysis software, SVCell™.

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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.

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Early access to next generation, time-lapse microscopy image analysis software now available to scientists

SVision LLC, an emerging leader in learning technologies for image recognition applications, has begun enrollment of the Early Adopter Program for its SVCell-Live software. The live cell module extends the capability of the ‘teachable’ SVCell software to address time-lapse microscopy applications. The SVCell-Live software automatically detects and tracks cells or subcellular objects in time-lapse images. It can define an accurate boundary for the object over time for kinetic shape analysis, and also model the kinetic gain or loss of fluorescence. It provides kinetic detection, tracking, measurements, modeling, 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. The software achieves accurate and robust performance enabled by SVision’s next generation kinetic recognition technologies, partially developed under three NIH SBIR programs.

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SVision LLC to launch SVCell™, ‘teachable’ recognition software for versatile microscopy image analysis

Scientists can now teach the computer to automatically detect, segment, measure, classify, analyze and discover cellular and subcellular phenotypes and events in their unique microscopy imaging experiments with a simple “teach by example” interface — guided by their biological knowledge rather than image processing expertise.

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Third in a Series of NIH Research Grants to Support Development of Next Generation Image Recognition Technologies for Live Cell Assays

SVision LLC, an emerging leader in image recognition and learning technologies, has received another Phase I Small Business Innovation Research (SBIR) Grant from the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH).

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Research Grant Will Extend Flexible Recognition and Quantitative Analysis Capabilities to Support Cell Biology Research

SVision LLC, an image informatics company developing flexible microscopy image recognition and quantitative analysis software for life science applications, has received a Phase I Small Business Innovation Research (SBIR) Grant from the National Institute of General Medical Sciences (NIGMS) of the National Institute of Health (NIH).

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Access to advanced technology for the simple and intuitive recognition and quantitative analysis of data from microscopy images soon available to a limited number of qualified collaborators

SVision LLC, an image informatics company developing flexible image recognition and quantitative analysis software for life science applications, has started the enrollment of its Early Adopter program for the company’s initial product, SVCell™.

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