Through this acquisition mode, significant increases in frame rate are accomplished by “fooling” the sensor into thinking it smaller than it actually is. In standard sub-array/ ROI readout mode, each frame still carries the time overhead to readout all pixels to the left and right of the selected area and to vertically shift all pixels above and below the selected area. The charge from these pixels is then dumped before an image is sent from camera to PC. In cropped sensor mode, the number of pixel readout steps outside of that required to readout out the requested sub-array is significantly reduced, resulting in markedly higher frame rates.
However, this mode requires that light is not allowed to fall onto the area of the sensor outside of the defined active sub-area. In optical microscopy, this can be realized in conjunction with the new OptoMask accessory, which inserts easily between the microscope output and the camera. Using the OptoMask, a sub-array can be readily defined through positioning of the masking blades, and a cropped area matched to this in software.
The iXon Ultra now comes with ‘Optically Centered Crop Mode’, which gives the user the option to break away from the corner tethered requirement of standard crop mode and select a number of pre-defined ROIs that are located in the center of the image field. This is achieved with only minimal sacrifice in achievable frame rate, for example a 128 x 128 optically Centered ROI delivering 697 fps (iXon Ultra 888). Optically centering of the ROI makes this mode extremely appealing to a number of microscopy techniques, including ‘pointillism’ live cell super-resolution microscopy. For example, the camera can be operated in full resolution at a frame rate suited to generation of fixed cell super-resolved images, then Optically Centered Crop Mode can be invoked with a ROI for generation of super-resolved live cell images, showing dynamic events.
Linear - In response to considerable demand from our customers, Andor have set about a detailed analysis of the EM voltage dependence, and have successfully converted the relationship between EM gain and the EM software setting into a linear one.
Real - Importantly, the true EM gain (i.e. the absolute signal multiplication factor) is selected directly from the linear gain scale. No more guesswork with arbitrary gain units across a non-linear scale - the gain you ask for is the gain you get. Select the best gain to overcome noise and maximize dynamic range.
Temperature Compensated - Although EM gain is temperature dependent, Andor's real/linear gain calibration extends to any EMCCD cooling temperature. Selecting x300 gain software setting @ -50ºC, or at -100ºC gives the same x300 true EM gain. Importantly, this means that there is no need to recalibrate EM Gain on each use in multi-user laboratories and facilities.
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It has been observed that EMCCD sensors, more notably in cameras that incorporate L3Vision sensors from E2V, are susceptible to EM gain fall-off over a period of time.
It is important to note that the ageing effect applies to any EMCCD camera, by any manufacturer, that incorporates these L3Vision sensors. As such, at time of writing, any camera on the market that offers back-illuminated EMCCD technology will be subject to a gain ageing effect which has bearings on the long term quantitative reproducibility of data. If left unchecked, this ageing phenomenon has the potential to significantly compromise the long-term quantitative reliability of EMCCD cameras. Fortunately, if these highly sensitive sensors are used with due care and attention, ageing can be minimized and should not present any real problem to the user.
An E2V technical note has been written on this phenomenon, entitled: ‘An Overview of the Ageing Characteristics of L3Vision™ Sensors’. This can be downloaded from the E2V website.
Andor have developed a unique and patented method of user-initiated EM gain self-recalibration. Even after exercising due care during usage and availing of the above internal restrictions, the EM gain may deplete over an extended period of time. The EMCAL™ self-recalibration process is very easily initiated by the user. At the touch of a button, a routine is triggered that measures EM gain and uses the iXon in-built temperature compensated linear gain scales to reset the EM gain calibration (if required), to deliver the true values requested on the software scale. EMCAL™ aims to markedly prolonged operational lifetime and quantitative reliability of the technology, and circumvent the need to return to the factory for recalibration.
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Offering extremely low clock induced charge and darkcurrent specifications, iXon X3 897 and 888 models are the most effective EMCCD cameras on the market for single photon counting acquisition. Single photon counting offers the advantage that the multiplicative noise associated with the EM amplificaon process is overcome, resulting in a factor 1.41x (SQRT 2) improvement to the signal to noise ratio (SNR).
The iXon EMCCD offers intuitive photon counting modes, either as a real time acquisition or as a post-processing step. OptAcquire™ can be used to first optimize the camera for photon counting acquisition.
As a post-processing analysis, the user holds the flexibility to ‘trial and error’ photon count a pre-recorded kinetic series, trading-off temporal resolution vs SNR by choosing how many images should contribute to each photon counted accumulated image. For example, a series of 1000 images could be broken down into groups of 20 photon counted images, yielding 50 time points. If it transpires that better SNR is required, the original dataset could be re-treated using groups of 50 photon counted images, yielding 20 time points.
Post-process’ Photon Counting offers the ability to switch between high SNR or high temporal resolution without loosing original data.
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New recursive averaging and frame averaging functions for improved signal to noise ratio, which can be applied in real time with minimal impact on image display rate. Recursive filter produces a running average, each output frame consisting of an average of existing and some previous images, as per the following equation:
Iout(n) = Iout(n-1) + [Vin(n) – Vout(n-1)] / F
Iin(n) = Latest image in series
Iout(n-1) = Previous output image
Iout(n) = Current recursive averaged output image
F = Averaging factor
Recursive averaging can produce an improved signal to noise in the image whilst maintaining the native frame rate. However, recursive filtering is not recommended for following highly dynamic events, since smearing within the image is likely.
The Frame Average filter improves signal to noise by yielding an arithmetic mean output image for every ‘F’ number of images input, as per the following equation:
Iout = [Iin(1) + ... + Iin(F)] / F
Iin(1) = 1st input image of series
Iin (F) = last input image in series
Iout = Frame Averaged output image
F = Number of images included in average series
This will also reduce the perceived effective frame rate by a factor of ‘F’. Frame Averaging is suited to dynamic events that can be temporally sampled by a ‘camera frame rate’ divided by ‘F’ rate of image output. However, if events occur faster than this, resulting in imaging smearing, either reduce the value of ‘F’ or deactivate completely.
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