Camera options for Zaber Nucleus microscopes

Property	Why it matters	What to look for
Quantum Efficiency	Better light gathering efficiency improves detection of weak signals and helps increase throughput by capturing bright images with short exposure times.	Higher is better
Read Noise	High contrast images with less noise improves detection of weak signals.	Lower is better
Temporal Dark Current	Lowers noise floor on long exposure images for improved detection of low intensity signals	Lower is better
Absolute Sensitivity Threshold	The lowest intensity signal which can be reliably detected above the noise floor. Useful for evaluating trade-offs between sources of image noise and light gathering efficiency.	Lower is better
Pixel Size	Larger pixels capture more light at the expense of resolution. Pixels smaller than the diffraction limit will not improve image resolution.	Application Dependent
Sensor Size	Larger sensors enable a larger field of view for faster scanning of large areas. A sensor much larger than the field number wastes sensor area.	Application Dependent

Table 1. Summarized camera properties and why they matter.

Color vs Monochrome

Color camera pixels are restricted to red, green or blue wavelengths (RGB), while monochrome camera pixels gather light from their full range of wavelengths at every pixel. This enables monochrome cameras to make better use of available light, resulting in superior low-light imaging capabilities.

Since color cameras only gather red, green or blue light at each pixel, reconstructing an image with all three wavelengths for every pixel requires processing to infer the missing values based on the values of adjacent pixels. This interpolation process results in a loss of effective spatial resolution. Interpolation is not required for monochrome cameras, resulting in greater spatial resolution (e.g. 12- and 16-bit depths).

For fluorescence microscopy, monochrome cameras are strongly recommended as they will deliver better spatial resolution and have greater light gathering efficiency over a wider range of wavelengths than colour cameras.

Pixel size, camera resolution and sensor size

Pixel size, camera resolution, and sensor size are traded off against each other. For a given sensor area, a sensor with larger pixels will capture more light per pixel but will output lower resolution images. A higher resolution sensor may capture more detail, but its smaller resolution pixels will not collect as much light.

Select your camera to match your optics. A camera with a sensor that is larger than your field number will result in wasted area on the sensor. A camera with a sensor that is much smaller than your field number will restrict your field of view, increasing your scanning time for a given sample area. Increasing image sensor resolution at the expense of smaller pixel sizes will cease to deliver an increase in spatial resolution once the pixel size shrinks below the resolution of your optics.

On-camera pixel binning is a useful capability which can combine groups of adjacent pixels into a single large virtual pixel. While this will decrease the resolution of the image captured, it will enable higher frame rates and a lower absolute sensitivity threshold. This increased speed and sensitivity is ideal for investigating phenomena like blood flow and intracellular Ca2+ dynamics. On-sensor binning is more effective at reducing noise than binning carried out in the camera's image processing system.

Sensitivity and read noise

Quantum Efficiency (QE) is a measure of how efficiently an image sensor can convert incoming photons into an output signal. It is widely used as a measure of sensitivity. Quantum efficiency is wavelength dependent, and peaks around 525 nm. Innovations in pixel design and sensor manufacturing techniques have yielded improvements in overall light gathering efficiency of newer sensors, and extended their useful wavelength range further into the near-infrared. Selecting a camera with a high QE for the emission wavelengths of your fluorophores will yield a higher intensity signal and enable shorter exposure times.

Figure 2. Quantum efficiency of CC01 (FLIR Blackfly camera) compared to emission wavelengths and relative illumination intensities of common fluorophores.

Read-noise is a measure of how accurately the charges on a sensor are converted into a digital signal. This translates into more reliable detection of lower intensity signals above the noise floor of the image. The weakest signal that can be reliably distinguished from the image noise is the Absolute Sensitivity Threshold (AST). The lower a camera's AST is, the weaker the signal it can reliably detect.

Over long exposures, CMOS image sensors will slowly accumulate random Temporal Dark Noise (TDN). Image stacking techniques developed by deep-space astronomers have overcome this phenomenon by leveraging the low read noise of CMOS sensors. Capturing several shorter duration exposures and averaging them results in the random TDN being averaged out, while only the desired signal remains.

Triggering

Zaber devices with IO ports can be set to trigger cameras via our free Zaber Launcher software. The Zaber multi-dimensional acquisition tool can use IO camera triggering to automate the acquisition of large, complex datasets. IO triggering is extremely low latency and is ideal for high throughput applications requiring tight synchronization.