Besides offering the highest EMCCD performance in the industry, the iXon EMCCD offers an advanced set of innovative features, developed as a direct response of listening to our customers. Some of the innovations of the iXon EMCCD Camera are outlined below and are common to both the new iXon Ultra and iXon3 models.
The control architecture of the iXon is extremely flexible, meaning the camera can be optimized for a wide variety of quantitative experimental requirements, ranging from single photon counting through to slower scan, 16-bit dynamic range measurements. However, we are starkly aware that optimizing EMCCD technology is far from trivial, with various control parameters trading off between camera performance characteristics. As such, we have developed OptAcquire™, a unique interface whereby a user can choose from a pre-determined list of nine camera set-up configurations. The user need only choose how they would like their camera to be optimized, e.g. for ‘Sensitivity & Speed’, ‘Dynamic Range & Speed’, ‘Time Lapse’. Parameters such as EM gain, vertical shift speed, vertical clock amplitude, pre-amp sensitivity and horizontal readout speed will then be optimized accordingly, ‘behind the scenes’. Furthermore, the option exists for the user to define their own additional configurations to add to the list.
iXon offers the capability to quantitatively capture and present data in units of electrons or photons, this important conversion applied either in real time or as a post-conversion step. The standard way to present quantitative data in scientific detectors has been in units of ‘counts’, relating to the digitized steps of the Analogue to Digital Converter (ADC) used in the camera. Each Analogue to Digital Units (ADU) step relates to a precise number of ‘photo-electrons’ which were generated originally from photons striking and being captured by the detector pixel. In the iXon, this conversion factor is very accurately recorded within the camera. Knowing this value, alongside the EM gain (RealGain™) and baseline (bias) offset, facilitates back calculation from the signal in ADU counts per pixel to the signal in electrons per pixel. Furthermore, knowledge of the Quantum Efficiency (QE) and light throughput properties of the camera at each wavelength enables this process to be taken a step further, allowing the signal to be estimated in photons incident at each pixel, provided the spectral spread of the signal is not too broad. The Count Convert functionality of the iXon provides the flexibility to acquire data in either electrons or incident photons, with negligible slow down in display rate. Furthermore, the option exists to record the original data in counts and perform this important conversion to either electrons or photons as a post-conversion step, while retaining the original data. • Quantify data in electrons or incident photons • Convenient estimate of sample signal intensity at the detector • Real time or post-convert • Reference between different samples, users and set-ups • Meaningful signal relating to PALM/STORM localization accuracy
Low light imaging before and after application of the iXon Spurious Noise Filter – spurious events (photons or remaining CIC) are identified and filtered from background.
While the iXon EMCCD range offers the lowest CIC and darkcurrent background noise on the market, it can still be desirable to have the optionally filter the remaining events to give as ‘black’ a background as possible, eradicating any remaining such ‘salt and pepper’ noise. It is important to utilize noise selection and filter algorithms that are intelligent enough to accomplish this task without impacting the integrity of the signal itself. This is realized through the new Spurious Noise Filter (SNF) functionality of iXon, which offers the user a choice of advanced algorithms to try. SNF can be applied either in real time or as a post-processing step. The latter option holds the distinct benefit that the raw untreated data is preserved, such that a judgment can be made as to whether a particular algorithm has been effective in selectively identifying and removing spurious background events within a data set. N.B. Use of SNF is absolutely NOT recommended for single photon counting experiments
Cropped Sensor Mode. The active imaging area of the sensor is defined in a way that only a small section of the entire chip is used for imaging. The remaining area has to be optically masked to prevent light leakage and charge spill-over that would compromise the signal from the imaging area. By cropping the sensor one achieves faster frame rates because the temporal resolution will be dictated by the time it requires to read out small section of the sensor.
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.
Frame rates achievable by the iXon Ultra 897 under both ‘Standard’ ROI and ‘Cropped Sensor’ modes of readout
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.
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. EMCAL™ 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.
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 resolutionwithout loosing original data.
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)] / FIin(n) = Latest image in seriesIout(n-1) = Previous output imageIout(n) = Current recursive averaged output imageF = Averaging factorRecursive 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)] / FIin(1) = 1st input image of seriesIin (F) = last input image in seriesIout = Frame Averaged output imageF = Number of images included in average seriesThis 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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