Instrumentation Noise Equivalent Exposure Research Articles

Experimental and theoretical performance analysis for a CMOS-based high resolution image detector.

Increasing complexity of endovascular interventional procedures requires superior x-ray imaging quality. Present state-of-the-art x-ray imaging detectors may not be adequate due to their inherent noise and resolution limitations. With recent developments, CMOS based detectors are presenting an option to fulfill the need for better image quality. For this work, a new CMOS detector has been analyzed experimentally and theoretically in terms of sensitivity, MTF and DQE. The detector (Dexela Model 1207, Perkin-Elmer Co., London, UK) features 14-bit image acquisition, a CsI phosphor, 75 µm pixels and an active area of 12 cm × 7 cm with over 30 fps frame rate. This detector has two modes of operations with two different full-well capacities: high and low sensitivity. The sensitivity and instrumentation noise equivalent exposure (INEE) were calculated for both modes. The detector modulation-transfer function (MTF), noise-power spectra (NPS) and detective quantum efficiency (DQE) were measured using an RQA5 spectrum. For the theoretical performance evaluation, a linear cascade model with an added aliasing stage was used. The detector showed excellent linearity in both modes. The sensitivity and the INEE of the detector were found to be 31.55 DN/µR and 0.55 µR in high sensitivity mode, while they were 9.87 DN/µR and 2.77 µR in low sensitivity mode. The theoretical and experimental values for the MTF and DQE showed close agreement with good DQE even at fluoroscopic exposure levels. In summary, the Dexela detector's imaging performance in terms of sensitivity, linear system metrics, and INEE demonstrates that it can overcome the noise and resolution limitations of present state-of-the-art x-ray detectors.

SU‐E‐I‐22: Performance Evaluation of a Commercial CMOS Detector for Dynamic High‐Resolution Imaging

Purpose: Present state‐of‐the art flat‐panel detectors have limitations in terms of noise and resolution for dynamic imaging. With recent developments, CMOS‐based detectors show promise to fulfill the ever increasing need for better image quality. Here, we evaluated a CMOS‐based detector by measuring its sensitivity, MTF, DQE and INEE. Methods: The detector (Hamamatsu Model # C10901D‐40) featured 12‐bit image acquisition, CsI phosphor, 100 μm detector pixel pitch and an active area of 9.7cm × 6.7cm and had a maximum frame rate of 30 fps. The sensitivity and instrumentation noise equivalent exposure (INEE) were calculated using flat‐field images taken at various exposures (4.2 μR to 334 μR). The detector resolution was evaluated by measuring the modulation transfer function (MTF) using a tilted edge. The noise power spectra (NPS) and detective quantum efficiency (DQE) were measured using the RQA5 spectrum for three different exposures (4.2 μR, 16.5 μR and 174 μR). Results: The signal vs. exposure curve showed excellent linearity of the detector and the sensitivity of the detector was found to be 5.8 DN/μR. The slope and the intercept of the variance vs. exposure curve were used to calculate the INEE of the detector, which was found to be 7.46 μR The measured MTF values were 0.61, 0.21 and 0.07 at 10%, 50% and 90% of the Nyquist frequency of 5 cycles/mm. The corresponding values of the DQE at these indicated frequencies were 0.47(0.56), 0.19(0.32) and 0.03(0.09) at 4.2 μR (16.5 μR). Conclusion: The imaging performance of Hamamatsu detector was evaluated in terms of sensitivity, linear system metrics and INEE. The INEE of this detector appears higher than desirable for fluoroscopy, but the detector shows good DQE at high exposure when the effect of the high instrumentation noise is not significant.(Support: NIH grants R01EB002873 and R01EB008425) NIH grants R01EB002873 and R01EB008425

TU-A-116-07: Comparison and Evaluation of Commercially Available CMOS X-Ray Detectors for Neurological Endovascular Image Guided Interventions (neuro-EIGI' s)

Purpose: To evaluate three commercially available CMOS x-ray detector systems as potential dual fluoroscopic and angiographic, high-resolution, ROI detectors for neuro-endovascular image-guided interventions (neuro-EIGIs) and to compare them to other experimentally evaluated or simulated neuro-EIGI detectors. Methods: Each CMOS detector was exposed to a standard RQA5 x-ray spectrum obtained by adding 21 mm of aluminum to a 70 kVp x-ray beam. Flat-field images were acquired by each detector and exposure per frame was determined using an ion chamber. From these images and exposures, sensitivity in digital numbers (DN/μR) and instrumentation noise-equivalent exposure (INEE) was found for each detector. These values were used to compare the three commercial detectors to other neuro-EIGI detectors previously built or simulated. Results: Detector A has a 12-bit ADC, a pixel size of 100 μm, and a full well capacity (FWC) of 2.2 million electrons (Me-). The sensitivity was found to be 5.8 DN/μR and the INEE was found to be 7.58 μR. Detector B has a 14-bit ADC, a pixel size of 75 μm, and a FWC of 0.36 Me-for the high sensitivity mode and 1.4 Me-for the high saturation mode. The sensitivity was found to be 28.9 DN/μR and the INEE was found to be 2.04 μR in the high sensitivity mode. Detector C has a 14-bit ADC, a pixel size of 100 μm and a FWC of 1.5 Me-. The sensitivity was found to be 15.1 DN/μR and the INEE was found to be 3.04 μR. The previous neuro-EIGI detectors had similar sensitivities of 10s–100s DN/μR, but much lower INEEs of <0.2 μR. Conclusion: While the commercial CMOS x-ray detectors are improving, it remains a desirable goal to further reduce the commercial detector pixel size and instrumentation noise to approach the values seen with the previously built and simulated neuro-EIGI detectors. Supported by NIH Grant 2R01EB002873 and an equipment grant from Toshiba Corporation.

Design, Characterization, and Modeling for a Modular High-Resolution Solid-State X-Ray Image Intensifier (SSXII)

A high resolution x-ray imaging system designated the solid state x-ray image intensifier (SSXII) is being developed as a potential replacement of conventional lower-resolution x-ray detectors for neurovascular interventions. The SSXII consists of a CsI(Tl) phosphor to convert x-rays to light, a fiber optic taper to extend the field-of-view and to couple the phosphor to an Electron-Multiplying CCD (EMCCD) which has a built-in gain to boost the signal above the read-out noise floor. A parallel cascade linear-system model is explored and applied to quantitatively analyze the signal and noise transfer at each stage, and optimize the detector performance. The modulation transfer function (MTF), detective quantum efficiency (DQE) and frequency dependent instrumentation noise equivalent exposure (INEE) can be obtained from the theoretical model and experimental measurement. Agreement of these results validates the effectiveness of the model. Finally, compared with the traditional flat-panel detector (FPD), the SSXII exhibits better performance with higher spatial resolution, higher DQE and lower INEE.

TU‐C‐211‐02: Characterizing the Dynamic Range and Noise Performance of a High‐Resolution EMCCD‐Based X‐Ray Detector Having Large Variable Electronic Gain Enabling Use in Both Fluoroscopy and Angiography

Purpose: To quantitatively characterize the dynamic range and noise performance of a new custom‐built, 1k by 1k, 26.4 micron square pixel, high‐resolution, solid‐state EMCCD‐based x‐ray detector. Methods: We performed two sets of experiments: higher‐exposure angiographic imaging with lower gain (&lt; 200), and lower‐exposure fluoroscopic imaging with higher gain (&gt; 200). For each experiment, 150 flat‐field images are acquired over the range of exposures for each multiplication gain. Average signal digital number (DN) versus exposure, and average variance (DN) versus exposure or signal are plotted and linearly fitted to quantitatively characterize the electronic gain, background or dark noise equivalent rms electrons, and instrumentation noise equivalent exposure (INEE), respectively. Results: For the low gain measurements, the noise electron rms value and INEE decreases with increasing gain virtually eliminating the effect of read‐noise, which is the main source of noise for conventional detectors. When the gain is increased for the low exposure measurements, dark noise from dark current and clock induced charge (CIC), which are constant with gain, become dominant and set the detection limit. With the same procedure, an additional experiment is performed to evaluate the dark noise and INEE at high gain with cooling. At room temperature, the dark noise is 1.03 e‐ rms and the INEE is 1.46 microR. Cooling the sensor effectively reduces the noise electrons (0.66 e‐ rms at 200mA pelticooler current and 0.50 e‐ rms at 400mA pelticooler current) and INEE (0.52 microR at 200mA pelticooler current and 0.33 microR at 400mA pelticooler current). Conclusions: The EMCCD‐based x‐ray detector with large variable gain has linear performance over a wide range of exposures with a low noise floor that can be further decreased by moderate cooling. The INEE for this unique detector is substantially less than the 2 to 3 microR of conventional flat panels.Support: NIH Grants R01‐EB008425, R01‐EB002873

MO‐E‐204B‐01: JUNIOR INVESTIGATOR WINNER: A New Simple, Accurate, and Quantitative Approach for Routine Quality Assurance in Digital Radiography

Purpose: We report on a new approach for measuring the MTF, instrumentation‐noise‐equivalent exposure (INEE), and DQE that is easily implemented, highly accurate, and does not require specialized measurement devices. No slits, edges, alignment devices, or other costly accessories are needed. Method and Materials: A method has been developed to obtain the MTF, INEE, and DQE using only the noise characteristics in dark‐ and flat‐field images. For demonstration, measurements were done on three different detector technologies: an x‐ray image intensifier, a flat‐panel detector, and a solid‐state x‐ray image intensifier. Ten dark‐field and flat‐field images (obtained at one exposure level using RQA 5) were acquired according to standard guidelines and the NPS was measured for each set of images. The electronic part of the NPS (constant, irrespective of exposure) and the quantum part of the NPS (proportional with exposure) could then be separated. MTFs were determined from the quantum part of the NPS using the new noise‐response (NR) method. Frequency‐dependent INEEs were measured by determining the exposure where quantum and electronic noise would be equivalent, thereby quantifying the quantum‐limited operating range of the detector. DQEs were determined from the measured MTFs and NPSs. A software package was written to automate the analysis. Results: Using this simplified approach, we observed agreement within 5% at the detector Nyquist frequency (even better agreement at lower spatial frequencies) with the most rigorous metric measurement methods. Measurements took less than 10 minutes per detector and were stable over a three‐month period, indicating no changes in, or problems with, detector performance. Conclusions: This work describes a simple technique for quantitative measurement of detector performance in terms of resolution (MTF), noise (INEE), and signal‐to‐noise ratio (DQE) that can be practically implemented into routine QA programs to assist in the verification of proper imaging system performance. (Support: NIH Grant RO1EB008425)

WE-E-201C-06: The Next Generation Solid State X-Ray Image Intensifier (SSXII)

Purpose: We report on new advancements with a solid state x‐ray image intensifier (SSXII) to expand the field‐of‐view (FOV) and improve detector performance. Method and Materials: The SSXII is a new high‐resolution, high‐sensitivity radiographic and fluoroscopic imager based on electron‐multiplying CCDs (EMCCDs), which views a CsI:Tl phosphor through a fiber optic taper (FOT). The SSXII has demonstrated the capabilities to significantly improve upon the inherent limitations of current state‐of‐the‐art x‐ray image intensifiers and dynamic flat panel detectors(FPD), with superior performance in terms of MTF, instrumentation noise, and DQE. To expand the FOV, a modular array has been constructed. The EMCCD camera electronics have been designed to enable a 2 × 2 abuttable array configuration. The 27 mm center‐to‐center distance enables use of 3.4:1 magnification ratio FOTs, thereby providing a FOV of 5.44 × 5.44 cm (an increase in area of 290% over the initial single module prototype). Larger arrays can be constructed. Performance of this next generation SSXII was extrapolated based on measured MTFs and transmission efficiencies of the individual components that comprise the detector.Results: Calculations indicate an averaged improvement in the MTF of a factor of 1.2 across the higher spatial‐frequency range (5 to 10 cycles/mm). X‐ray sensitivities are expected to increase by 40% due to a reduction in the FOT magnification ratio (from 4:1 to 3.4:1). The instrumentation noise equivalent exposure (INEE) was calculated to decrease from 0.2 to 0.03 μR, which is two orders of magnitude lower than present FPDs. The DQE was determined to improve by an averaged factor of 2.2 from 5 to 10 cycles/mm. Conclusions: With an expanded FOV, the SSXII is a promising candidate to replace existing state‐of‐the‐art detectors, providing improved resolution, lower instrumentation noise, and better signal‐to‐noise ratio performance. (Support: NIH Grant RO1EB008425)

WE-C-304A-08: The Instrumentation Noise Equivalent Exposure (INEE): Including Conversion, Secondary Quantum, Structure and Electronic Noise

Purpose: To provide a quantitative and clinically relevant measure of the instrumentation noise of digital x‐ray imagers, using the Instrumentation Noise Equivalent Exposure (INEE). Method and Materials: The NPS was “decomposed” into constituent elements of primary quantum noise,Poisson excess noise (Swank noise), secondary quantum noise, structure noise and additive electronic noise using a plot of the total measured NPS versus exposure and using known relationships based on a generalized parallel cascade model analysis. The INEE was determined by measuring the exposure at which the total instrumentation noise and primary quantum noise were equivalent. Exposures at the INEE correspond to a drop in DQE of one‐half. To demonstrate the usefulness of this new metric, the spatial‐frequency‐dependent INEE was measured on a clinical (indirect) dynamic flat panel detector(FPD) with a pixel pitch of 194 μm and a 600 μm thick CsI:Tl phosphor.Results: The INEE was measured to be 2.0, 7.1 and 75 μR at 0, 1 and 1.2 cycles/mm, respectively. Above 1.2 cycles/mm the detector was instrumentation‐noise‐limited at all exposures, resulting in a degradation in image quality beyond that dictated by the noise in the incident x‐ray quanta alone. Hence, above 1.2 cycles/mm the DQE was always less than half the maximum value. Conclusions: In this work, all sources of instrumentation noise were incorporated into the INEE formalism, consisting not only of the additive electronic noise, but also including the Poisson excess noise (i.e. noise resulting from the phosphor), secondary quantum noise (i.e. noise resulting from the conversion and transmission of quanta) and structure noise (i.e. noise resulting from variations in the detector sensitivity). The INEE can be used to assess quantum‐noise‐limited operation at all spatial frequencies of interest by characterizing the total instrumentation noise in terms of equivalent detector entrance exposure. (Partial support: NIH grants R01EB008425, R01EB002873, R01NS43924)

TH‐C‐210A‐04: New High Resolution Dynamic Detectors and Flow Modifying Stents for Neuro‐Endovascular Image Guided Interventions

As the field of minimally invasive endovascular image‐guided interventions (EIGI) advances, there has been progress in the development of new endovascular devices such as the asymmetric vascular stent for treatment of aneurysms as well as progress in the image guidance systems needed to improve both the diagnoses and interventions and the methods used to evaluate the improved imaging performance. High resolution imaging systems with MTFs extending past 8 Lp/mm and with ability to visualize not only radioopaque markers but the detailed structure of devices such as stents have motivated the development of new asymmetric devices such as the blood flow modifying asymmetric vascular stent (AVS). The AVS has now come through a number of generations from balloon expandable stainless steel strutted structures with laser micro‐welded mesh flow diverters to new super‐elastic nitinol closedcell self‐expanding stents with organic material flow diverters. The methods of laser machining, surface finishing, and deployment will be described with progress in animal models reported. In parallel with advances in EIGI devices has come new high resolution detector development. The detectors have a unique combination of features such as far superior spatial resolution compared with conventional dynamic flat panel detectors, large dynamic range of sensitivity with negligible lag and ghosting to enable both fluoroscopy and angiography, and low noise to enable quantum limited performance over the full useful range including during lowdose fluoroscopy. The Micro‐Angiographic Fluoroscope (MAF) consists of an x‐ray converter phosphor sensed by a micro‐channel plate light image intensifier which is in turn coupled to a high performance CCD camera using a fiber optic taper. The MAF is a region of interest (ROI) imager with 4 cm field of view centered at the interventional site and may be moved in front of a larger conventional detector when improved resolution is needed. The Solid State X‐ray Image Intensifier (SSXII) while having much of the benefits of the MAF in superior imaging capability achieves its great sensitivity using only electron multiplying CCD sensors. An array design is being developed so that the imaging FOV may be expanded by adding modules each with its own EMCCD‐based detector. To more fully characterize detectors, new evaluation methods are being explored. For example, the accurate determination of MTF from measurements of noise only, without the need for a slit or edge will be reported. Also from a careful analysis of noise, the exposure range for detector quantum limited performance can be well demarcated by the instrumentation noise equivalent exposure (INEE). Finally, more realistic linear system parameters that include focal‐spot size, geometry, and scatter provide generalized MTFs and DQEs or GMTFs and GDQEs. All told, there is much happening in EIGI.Learning Objectives1. Appreciate the progress being made in improved EIGI devices and in particular flow modifiers such as the asymmetric vascular2. stent (AVS) for aneurysm treatment.3. Understand the operation of new high‐resolution micro‐angiographic systems including the MAF and SSXII.4. Understand new objective image detector evaluations including INEE, GMTF, GDQE, and determination of MTF from noise5. measurements alone.(Supported in part by NIH Grants R01EB002873, R01 NS43924, R01EB008425, and the Toshiba Medical Systems Corp.)

Component analysis of a new Solid State X-ray Image Intensifier (SSXII) using photon transfer and Instrumentation Noise Equivalent Exposure (INEE) measurements.

The SSXII is a novel x-ray imager designed to improve upon the performance limitations of conventional dynamic radiographic/fluoroscopic imagers related to resolution, charge-trapping, frame-rate, and instrumentation-noise. The SSXII consists of a CsI:Tl phosphor coupled via a fiber-optic taper (FOT) to an electron-multiplying CCD (EMCCD). To facilitate investigational studies, initial designs enable interchangeability of such imaging components. Measurements of various component and configuration characteristics enable an optimization analysis with respect to overall detector performance. Photon transfer was used to characterize the EMCCD performance including ADC sensitivity, read-noise, full-well capacity and quantum efficiency. X-ray sensitivity was measured using RQA x-ray spectra. Imaging components were analyzed in terms of their MTF and transmission efficiency. The EMCCD was measured to have a very low effective read-noise of less than 1 electron rms at modest EMCCD gains, which is more than two orders-of-magnitude less than flat panel (FPD) and CMOS-based detectors. The variable signal amplification from 1 to 2000 times enables selectable sensitivities ranging from 8.5 (168) to over 15k (300k) electrons per incident x-ray photon with (without) a 4:1 FOT; these sensitivities could be readily increased with further component optimization. MTF and DQE measurements indicate the SSXII performance is comparable to current state-of-the-art detectors at low spatial frequencies and far exceeds them at higher spatial frequencies. The instrumentation noise equivalent exposure (INEE) was measured to be less than 0.3 μR out to 10 cycles/mm, which is substantially better than FPDs. Component analysis suggests that these improvements can be substantially increased with further detector optimization.

A practical exposure-equivalent metric for instrumentation noise in x-ray imaging systems

The performance of high-sensitivity x-ray imagers may be limited by additive instrumentation noise rather than by quantum noise when operated at the low exposure rates used in fluoroscopic procedures. The equipment-invasive instrumentation noise measures (in terms of electrons) are generally difficult to make and are potentially not as helpful in clinical practice as would be a direct radiological representation of such noise that may be determined in the field. In this work, we define a clinically relevant representation for instrumentation noise in terms of noise-equivalent detector entrance exposure, termed the instrumentation noise-equivalent exposure (INEE), which can be determined through experimental measurements of noise-variance or signal-to-noise ratio (SNR). The INEE was measured for various detectors, thus demonstrating its usefulness in terms of providing information about the effective operating range of the various detectors. A simulation study is presented to demonstrate the robustness of this metric against post-processing, and its dependence on inherent detector blur. These studies suggest that the INEE may be a practical gauge to determine and compare the range of quantum-limited performance for clinical x-ray detectors of different design, with the implication that detector performance at exposures below the INEE will be instrumentation-noise limited rather than quantum-noise limited.

SU‐DD‐A4‐06: Instrumentation Noise Equivalent Exposure (INEE): An Investigation of Spatial Frequency Effects

Purpose: To expand on previous development of the instrumentation‐noise equivalent exposure (INEE) metric which directly quantifies the quantum‐limited performance range of a detector in terms of entrance exposure, by investigating spatial frequency dependence. Method and Materials: The INEE formalism assumes the total noise of an x‐ray detector is proportional to the incident number of quanta, with an additive term representing contributions resulting from instrumentation‐noise sources. The INEE then represents the threshold exposure below which the detector's performance is no longer driven by quantum statistics, becoming instrumentation‐noise‐limited and is measured using output signal variance plot versus exposure, fitted to . Similarly, to provide a spatial frequency dependent INEE, INEE(u,v), the two‐dimensional NPS (i.e. the variance of image intensity divided among the various frequency components of the image) was measured and plot as a function of exposure at each spatial‐frequency and fit with NPS(u,v)=k(u,v)(Exposure+INEE(u,v)). Output signal variance and NPS were measured using 90 flat‐field images on a digital x‐ray detector according to IEC guidelines and using the RQA 5 spectrum. Results: The measured INEE(u,v) was radially symmetric with the lowest INEE values at low spatial‐frequencies with an increasing INEE at higher spatial‐frequencies. The frequency behavior was determined to be largely dependent on the blur and scattering of the phosphor as described by the detector MTF. Frequency independent INEE was determined to be the weighted mean of INEE(u,v) with k(u,v), over all spatial frequencies. Conclusion: The INEE metric addresses the need for a direct, quantitative measure of the quantum‐noise‐limited exposure range of x‐ray detectors by providing the threshold exposure at which the detector instrumentation‐noise exceeds the quantum‐noise. Frequency dependence was investigated to provide a greater understanding of this promising new metric.(Support: NIH Grants R01‐NS43924, R01‐EB002873, Toshiba Medical Systems Corporation).

MO‐E‐332‐07: Instrumentation Noise Equivalent Exposure (INEE) for Routine Quality Assurance: INEE Measurements On a Clinical Flat Panel Detector

Purpose: To measure the instrumentation‐noise equivalent exposure (INEE) of a clinical digital imaging system under various modes of operation. Method and Materials: The INEE is defined as the exposure at which the quantum‐noise equals the instrumentation‐noise and is measured from the plot of pixel gray‐level‐value variance versus detector entrance exposure. The intercept of such a plot represents the instrumentation‐noise in gray‐level values and the slope provides the conversion factor from these arbitrary units to equivalent exposure. Sequences of 90 flat‐field images in DA and DSA modes were acquired at 1 frame‐per‐second using a Varian PaxScan 2020 flat panel detector, both with image processing enabled and disabled. Image receptor input exposure was measured using an ionization chamber and effects of uncertainties in exposure calibration on the resulting INEE were investigated. Results: The INEE was observed to vary depending on the mode used and was measured to be 0.9±0.2 and 44±6 μR in DA and DSA modes, respectively, with image processing disabled. Exposure calibration error will result in additional proportionate INEE error. With image processing enabled the variance was highly nonlinear with exposure in DA mode indicating a need to have access to linear, unprocessed data. The difference in integration capacitance between DA and DSA modes, 0.5 and 4 pF respectively, helps explain the change in the INEE between these modes. Conclusion: INEE measurements were done on a clinical digital image receptor and were found to be dependent on the operational mode used. The importance of disabling image processing during INEE measurement was demonstrated. Due to the ease in gathering and analyzing the necessary data, we found the INEE to be a useful quality assurance tool for assessing a system's instrumentation‐noise in terms of a clinically relevant measure of exposure. (Support: NIH Grants R01‐ NS43924, R01‐EB002873, Toshiba Medical Systems Corporation).

MO-D-332-01: Noise Evaluation of a New Solid-State X-Ray Image Intensifier (SSXII)

Purpose: To measure the impact of thermal and multiplication‐excess noise and the instrumentation‐noise equivalent exposure (INEE) of a new solid‐state x‐ray image intensifier (SSXII) based on electron‐multiplying CCDs (EMCCDs). Method and Materials: The SSXII consists of a 350μm thick CsI(Tl) phosphor grown on a fiber‐optic plate optically coupled to a Peltier cooled EMCCD camera with a fiber‐optic input window via a 4:1 minifying fiber‐optic taper. The EMCCD provides signal multiplication gain prior to the read‐out electronics, thereby eliminating this primary noise source, effectively allowing for instrumentation‐noise free operation even at very low x‐ray exposures. Two additional potential noise sources, thermal and multiplication‐excess noise, were investigated. Thermal noise was determined using a linear fit of dark‐signal variance versus integration time at a constant readout rate. Multiplication‐excess noise was determined using signal variance normalized to gain versus signal plots. The gradient of a linear fit to this data at 1x gain as compared to higher gain values (up to 14x) was used to determine the excess noise factor (ENF). Overall noise‐performance was then determined using the INEE. Results:Thermal noise was measured to be < 2% of the maximal signal (12‐bits) with an EMCCD gain of 275x and an integration time of 30 ms, and is considered an upper bound under typical clinical operating conditions, indicating thermal noise has a negligible impact on overall image quality. The ENF was unity for the range of gains tested, suggesting the inherent excess noise of the electronic‐multiplication process has little effect when imaging secondary quanta from an x‐ray converting phosphor. An INEE of < 0.2μR further demonstrates the SSXII's capability to operate instrumentation‐noise free at very low x‐ray exposures. Conclusion: The SSXII provides quantum‐noise‐limited performance well below typical fluoroscopic exposure levels with negligible thermal and multiplication‐excess‐noise. (Support: NIH Grants R01‐NS43924, R01‐EB002873, Toshiba Medical Systems Corporation).

TH-C-L100F-02: Instrumentation Noise Equivalent Exposure (INEE) and the Effect of Detector Blurring and Image Post-Process Smoothing: A Simulation Study

Purpose: To investigate the behavior of Instrumentation-Noise-Equivalent Exposure (INEE) when there is detector blurring and image post-process smoothing. Method and Materials: INEE is the exposure at which detected quantum noise and instrumentation noise are equal, and below which the system becomes instrumentation noise limited. In order to understand the effect of detector blurring and post-process smoothing on the determination of INEE, Poisson-distributed random numbers (representing input x-ray quanta per pixel) were generated that simulate an ideal input x-ray image pattern. Blurring functions were simulated by Gaussian pointspread functions with different full-width-half-maxima (FWHM), defined in a 15 pixel × 15 pixel kernel. The reference pixel-size and x-ray fluence were selected following a set of measurements on a custom Microangiographic detector (43 μm square-image-pixels in 1024×1024 pixel matrix). A two-dimensional discrete convolution of the Poisson-distributed image with the Gaussian blurring function results in an image with reduced total-noise, but constant signal. The instrumentation-noise was simulated by an additive constant-variance and zero-mean noise. Addition of instrumentation noise after the blurring process simulates the detector-blurring case, whereas addition before the blurring process represents the image-post-process smoothing. This study assumed that the system has no secondary-quantum-sink and follows Poisson statistics throughout the imaging-chain. INEE was determined by calculating the signal-to-noise ratio (SNR) over a range of input exposures, and analyzed as a function of Gaussian-width and additivenoise levels. Results: The square-root of INEE is shown to increase linearly with detector-Gaussian-blur width, but is shown to be independent of image-post-process smoothing. For this particular study, a one-pixel increase in FWHM of the blurring function resulted in 1.5x higher output SNR. Conclusion: A simple simulation study was presented to demonstrate that the SNR-based practical measurement of INEE is independent of image-post-process smoothing in digital x-ray imaging systems. (Partial support: NIH R01-NS43924, R01-EB002873, Toshiba Corp.).