Presented by: Nicholas Beavers, Applications Specialist, Media Cybernetics
Webinar Date:
Wednesday, August 19, 2009 10:00am - 11:00am EST
Click here to register.
Imaging in the life and materials sciences has become completely digital and this transformation of visual imagery into mathematical constructs has made it commonplace for researchers to utilize computers for their day-to-day image analysis tasks. Along with this change comes the need to fully understand how image data is handled within a computer and how image processing methods can be applied to extract useful measurements and deeper understanding of image-based data.
Attendees at this live, interactive and highly instructional webinar will learn the basics of image processing as it applies to the life and materials sciences and will leave with confident answers to questions such as:Who should attend? Everyone who either performs digital imaging or needs to better grasp the processes that have been applied to images that are part of a lab’s research will benefit from attending this short web presentation.
Imaging in the life and materials sciences has become completely digital and this transformation of visual imagery into mathematical constructs has made it commonplace for researchers to utilize computers for their day-to-day image analysis tasks. Along with this change comes the need to fully understand how image data is handled within a computer and how image processing methods can be applied to extract useful measurements and deeper understanding of image-based data.
Attendees at this live, interactive and highly instructional webinar will learn the basics of image processing as it applies to the life and materials sciences and will leave with confident answers to questions such as:
- What is a digital image?
- What is bit depth and when does it matter?
- How do settings such as brightness, contrast, and gamma affect my images?
- What is background correction and how does it work?
- How do image processing filters work, such as sharpening, low-pass, median, and others?
- What are various ways of measuring image data, including distance, area, volume, roundness, roughness, intensity?
- How can we identify and count objects in images?
- How can fluorescence images be best visualized and measured?
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