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When to Use Machine Vision Cameras in Microscope
Situation #1: High Throughput Microscopy Applications with Automated Image Analysis Software
Machine vision cameras are ideally suited to applications which require high throughput, are not limited by low light, and where a human will not look at the raw data. Designers of systems where the acquisition and analysis of images will be automated must change their perspective of what makes a “good” image. Rather than optimizing for images that look good to humans, the goal should be to capture the “worst” quality images which can still yield unambiguous results as quickly as possible when analyzed by software. If you are using “AI”, a machine vision camera is worth considering.
A common example is imaging consumables to which fluorescent markers will hybridize to specific sites. To read these consumables, one must check each possible hybridization site for the presence or absence of a fluorescent signal.
Situation #2: When a Small Footprint is Important
The small size, integration-friendly features and cost effectiveness of machine vision cameras make them an attractive option for OEM devices where minimizing the device footprint and retail price are important considerations. How are machine vision cameras different from scientific cameras? The distinction between machine vision and scientific cameras is not as clear as it once was. The term “Scientific CMOS” (sCMOS) was introduced in the mid 2010’s as advancements of CMOS image sensor technology lead to the development of the first CMOS image sensor cameras that could challenge the performance of then-dominant CCD image sensor technology. These new “sCMOS” sensors delivered improved performance relative to the CMOS sensors that were prevalent in MV cameras of the time. Since then, thanks to the rapid pace of CMOS image sensor development, the current generation of MV oriented CMOS sensors boast impressive performance. There are now many scientific cameras with MV sensors, and many MV cameras with scientific sensors.