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Friday, October 4 • 12:10pm - 12:30pm
Poster Presentations in Exhibition- #5 Deep Learning Based Image Analysis in Laboratory Automation and In Vitro Diagnostics with COGNEX VisionPro ViDi Software Suite

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COGNEX Machine Vision systems are the gold standard on the Factory Automation floor and meanwhile also in Lab Automation environments. Traditional vision systems excel in gauging, measuring and precision alignment, but algorithms become challenging to program as the exceptions and defect libraries grow or different objects look similar which is often the case in Lab Automation and IVD applications.
Deep Learning-based image analysis combines the specificity and flexibility of human visual inspection with the reliability, consistency, and speed of computerized systems. With the introduction of Deep Learning we face new challenges, for example, the large number of images needed for proper training is not always available, the time to develop a highly accurate application is long, developing and maintaining the network requires a highly skilled individual or team and the black-box behavior of the system sometimes can’t earn the trust of the end-user.

Another interesting trend with the emergence of deep learning is that people start to neglect the traditional rule-based approach, but what we see is that rule-based vision and Deep Learning-based image analysis are complementing each other and enable us to solve more complex automation problems.
COGNEX VisionPro ViDi™ is a ready-to-use Deep Learning-based software suite dedicated to image analysis which can provide solutions for a wide range of applications in the life sciences field. It also provides seamless integration with our traditional rule-based vision tools as needed.
In our novel approach, we designed four specific Deep Learning tools which can be used to break down a complex problem to smaller and simpler steps to provide the final solution with a customized toolchain. Each tool is optimized for one specific task:
-Blue – Locate for feature location and verification
-Red – Analyze for segmentation and defect detection
-Green – Classify for scene and object classification
-Blue – Read for optical character recognition

This method allows us to build a solution with only a few hundred images, train and run the Deep Learning models locally on a single GPU system. It also makes it easier to localize any erroneous behavior in the system. The suite provides a graphical user interface for training and labeling with a handful of parameters to fine-tune the models. This feature can enable medical professionals without extensive Deep Learning knowledge to rapidly develop various Deep Learning-based applications where the experts can focus on optimizing, validating and deploying these solutions.
Applications where we successfully developed a solution with COGNEX VisionPro ViDi™:
-Deck inspection, Tube and Plate identification for medical instruments
-HIL Quality inspection of centrifuged blood samples
-Bacteria Classification
-Colony Counting / Classification

These examples highlight the potential of COGNEX VisionPro ViDi™ to be useful for a broad range of complex image analysis tasks within life sciences.


Jozsef Nagy, B.S.

Life Science OEM Project Manager, Cognex Corporation
Jozsef Nagy is a Project Manager at Cognex Corporation with 10 years of experience in the machine vision field. At Cognex, he is focused on integrating smart vision systems into medical instruments. Most recently, he has been leading the evaluation and deployment of Cognex deep learning-based... Read More →

Friday October 4, 2019 12:10pm - 12:30pm EDT
Washington Ballroom (5th Fl) - Courtyard Boston Downtown 275 Tremont Street, Boston, MA 02116