Polychromatic Spectra Research Articles

Effects of lead shielding on gamma radiation scatter energy spectrum during equine bone scintigraphy.

The main aim of this pilot study was to determine how the energy spectrum of scatter radiation emitted from horses after injection of the radiopharmaceutical 99mTechnetium-methyl diphosphonate (99mTc-MDP), changed behind lead shielding of varying thicknesses (0.25 mm, 0.35 mm, and 0.5 mm Pb thickness), and if beam hardening occurred. The effect lead shielding has on the emitted gamma radiation energy spectrum has not been documented. In particular, the presence of beam hardening effects behind lead shielding was investigated, to determine whether or not it could discourage the use of lead shields during bone scintigraphy in horses. Horses were injected intravenously with 99mTc-MDP, and energy spectra emitted from horses without lead shielding were recorded initially to determine the emitted scatter spectrum. Thereafter, different combinations of lead shields of the various thicknesses listed above, draped over the horse and on simulated personnel, were recorded. The energy spectra were obtained at different anatomical locations of five horses on five consecutive days with a pulse height (multichannel) analyser two and a half hours post-injection. Energy spectra recorded from horses without lead shielding showed polychromatic energy spectra that encompassed a large portion of predominantly lower scatter energies (averaging around the 88-94 keV peaks). Higher 99mTc- MDP peaks averaging at 139-143 keV (useful for gamma camera acquisition) were consistently seen in all recordings but made up a very small part of the emitted spectra. With the application of lead shielding, peaks of 83-86 keV, which coincided with K-edges of lead, occurred. No significant beam hardening effects behind lead shields of varying thicknesses were observed. Thus, the wearing of lead shields during bone scintigraphy of horses is encouraged.

The acceptor-donor pair recombination of beryllium-treated sapphires

Recently, the concept of Fe3+-Ti4+ mixed acceptor states in the energy band gap of sapphire has been proposed as the cause of blue coloration. The blue color in sapphire is faded and turns yellow by beryllium heat treatment. It has been revealed as the color center in Be-treated yellow sapphires. In this work, the mechanism of such phenomena was explained and discussed. The experiment was set by preparing sapphire samples from Songea, Tanzania, into four color groups (purplish blue, light blue, light yellow with dark zone, and light green). One sample from each group, altogether four, has been heat-treated with beryllium. The colors of Be-treated samples show fading of blue coloration and adding the yellow component to the samples. The analyses and spectroscopic testing were conducted on both the untreated and treated samples, in each group which consisted of one natural and one Be-treated sample. The content of color-related trace elements such as Be, Mg, Ti, Fe, and Cr was measured by the LA-ICP-MS. The oxidation state of Fe [III] was confirmed by X-ray absorption spectroscopy. Each color group showed quite similar UV–Vis–NIR absorption spectra for the natural and the Be-treated ones, regardless of differences in their color and treatment. However, their UV–Vis–NIR polychromatic excitation spectra were different, leading to the possible detection of blue color suppression due to the recombination of Fe3+-Ti4+ mixed-acceptor states by the Fe3+-Be2+ mixed donor states for Be-treated samples. Hence, the acceptor-donor pair recombination has been proposed for the blue color fading in beryllium-treated sapphire samples.

Non-linear fusion of dual-energy projections for XCT imaging of challenging components

The imaging of multi-material components having large changes in attenuation behaviour is widely regarded as a limitation of X-ray computed tomographic techniques. The use of Dual Energy X-ray Computed Tomography (DECT) is common in the field of medical imaging, providing many benefits to imaging and characterisation. However, multienergy methods such as DECT remain underutilised in the industrial sector. In this work, a novel measurement based multi-energy image fusion approach was evaluated using two radiographic image stacks acquired under two distinct polychromatic spectra; this fusion was then compared to the results of the individual high and low-energy datasets as well as their average. The implemented approach was tested using a Titanium (Ti) and Carbon Fibre reinforced Polymer (CFRP) double-step lap joint to evaluate performance. Results indicated improvements to contrast in Dual Energy fused radiographs, aiding the interrogation of complex components in 2D. The translation of these benefits into the Reconstructed CT volume showed promise for isolated material regions. It was established that careful parameter selection was needed to achieve optimum fusion results, as it was found that failure to do so, resulted in contrast suppression in regions of mixed materials. The process proposed here acts as a first foundational step into the fusion of multi-energy industrial X-ray computed tomography (XCT) datasets using standard XCT equipment. Further work will aim at refining and comparing it to other projection weighting functions and measures.

Development and validation of a simulation tool for K-edge Subtraction imaging with polychromatic spectra and X-ray photon counting detectors

In K-Edge Subtraction (KES) imaging the K-edge of a high-Z contrast medium is used to generate a differential image in which, in principle, only the contrast agent is visible, suppressing any background. A possible approach to KES imaging is by using polychromatic spectra and spectral X-ray photon counting detectors (XPCD). In this paper we present the development and validation of a simulation tool for KES imaging with spectral XPCD. In addition an analytical formula, based on theoretical considerations, is derived, that further supports the simulation results. The validation is made on experimental data obtained with an X-ray tube, an iodine-based contrast agent, and Pixirad-1/Pixie-III detection system.

Impact of Various Visible Spectra on Attached Microalgal Growth on Palm Decanter Cake in Triggering Protein, Carbohydrate, and Lipid to Biodiesel Production

Attached microalgal growth of Chlorella vulgaris on palm decanter cake (PDC) under irradiation with various visible monochromatic and polychromatic spectra to produce biodiesel was studied in this work. The results demonstrated that the white spectrum cultivation exhibited the highest microalgal density of 1.13 g/g along with 1.213 g/L day of microalgal productivity. Correspondingly, the biodiesel obtained was comprised mainly of C16 and C18 fatty acids, possessing a high cetane number and oxidation stability from the high saturated fatty acid content (70.38%), which was appealing in terms of most biodiesel production requirements. Nevertheless, the highest lipid content (14.341%) and lipid productivity (93.428 mg/L per day) were discovered with green spectrum cultivation. Blue and white spectra led to similar protein contents (34%) as well as carbohydrate contents (61%), corroborating PDC as a feasible carbon and nutrient source for growing microalgae. Lastly, the energy feasibilities of growing the attached microalgae under visible spectra were investigated, with the highest net energy ratio (NER) of 0.302 found for the yellow spectrum. This value outweighed that in many other works which have used suspended growth systems to produce microalgal fuel feedstock. The microalgal growth attached to PDC is deemed to be a suitable alternative cultivation mode for producing sustainable microalgal feedstock for the biofuel industry.

Feasibility of dual-energy CBCT by spectral filtration of a dual-focus CNT x-ray source.

Cone beam computed tomography (CBCT) is now widely used in dentistry and growing areas of medical imaging. The presence of strong metal artifacts is however a major concern of using CBCT especially in dentistry due to the presence of highly attenuating dental restorations, fixed appliances, and implants. Virtual monoenergetic images (VMIs) synthesized from dual energy CT (DECT) datasets are known to reduce metal artifacts. Although several techniques exist for DECT imaging, they in general come with significantly increased equipment cost and not available in dental clinics. The objectives of this study were to investigate the feasibility of developing a low-cost dual energy CBCT (DE-CBCT) by retrofitting a regular CBCT scanner with a carbon nanotube (CNT) x-ray source with dual focal spots and corresponding low-energy (LE) and high-energy (HE) spectral filters. A testbed with a CNT field emission x-ray source (NuRay Technology, Chang Zhou, China), a flat panel detector (Teledyne, Waterloo, Canada), and a rotating object stage was used for this feasibility study. Two distinct polychromatic x-ray spectra with the mean photon energies of 66.7keV and 86.3keV were produced at a fixed 120kVp x-ray tube voltage by using Al+Au and Al+Sn foils as the respective LE and HE filters attached to the exist window of the x-ray source. The HE filter attenuated the x-ray photons more than the LE filter. The calculated post-object air kerma rate of the HE beam was 31.7% of the LE beam. An anthropomorphic head phantom (RANDO, Nuclear Associates, Hicksville, NY) with metal beads was imaged using the testbed and the images were reconstructed using an iterative volumetric CT reconstruction algorithm. The VMIs were synthesized using an image-domain basis materials decomposition method with energy ranging from 30 to 150keV. The results were compared to the reconstructed images from a single energy clinical dental CBCT scanner (CS9300, Carestream Dental, Atlanta, GA). A significant reduction of the metal artifacts was observed in the VMI images synthesized at high energies compared to those from the same object imaged by the clinical dental CBCT scanner. The ability of the CNT x-ray source to generate the output needed to compensate the reduction of photon flux due to attenuation from the spectral filters and to maintain the CT imaging time was evaluated. The results demonstrated the feasibility of DE-CBCT imaging using the proposed approach. Metal artifact reduction was achieved in VMIs synthesized. The x-ray output needed for the proposed DE-CBCT can be generated by a fixed-anode CNT x-ray source.

A Data Transmission Method with Spectral Switches via Electroabsorption

In the past, the waveguide electroabsorption effect has generally been used as an intensity modulator for quasi-monochromatic light, such as lasers. Here, we study how this effect affects polychromatic light spectra. We find that for light with a Gaussian distribution spectrum, the spectral peak shift (red shift or blue shift) can be controlled by the magnitude of the applied voltage, as long as the center wavelength and the spectral band are properly selected. This result can be used as a data transmission scheme at the integrated chip level or in free space. It may offer a good option for some other light sources, such as low-cost LED or ELED (edge emitting LED), with wider spectral bandwidths.

A revised action spectrum for vitamin D synthesis by suberythemal UV radiation exposure in humans in vivo

Action spectra are important biological weighting functions for risk/benefit analyses of ultraviolet (UV) radiation (UVR) exposure. One important human benefit of exposure to terrestrial solar UVB radiation (∼295 to 315 nm) is the cutaneous synthesis of vitamin D3 that is initiated by the photoconversion of 7-dehydrocholesterol to previtamin D3 An action spectrum for this process that is followed by other nonphotochemical steps to achieve biologically active vitamin D3 has been established from ex vivo data and is widely used, although its validity has been questioned. We tested this action spectrum in vivo by full- or partial-body suberythemal irradiation of 75 healthy young volunteers with five different polychromatic UVR spectra on five serial occasions. Serum 25-hydroxyvitamin D3 [25(OH)D3] levels, as the most accurate measure of vitamin D3 status, were assessed before, during, and after the exposures. These were then used to generate linear dose-response curves that were different for each UVR spectrum. It was established that the previtamin D3 action spectrum was not valid when related to the serum 25(OH)D3 levels, as weighting the UVR doses with this action spectrum did not result in a common regression line unless it was adjusted by a blue shift, with 5 nm giving the best fit. Such a blue shift is in accord with the published in vitro action spectra for vitamin D3 synthesis. Thus, calculations regarding the risk (typically erythema) versus the benefit of exposure to solar UVR based on the ex vivo previtamin D3 action spectrum require revision.

Deep learning-based pupil model predicts time and spectral dependent light responses

Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 pm 1 K, 4983 pm 3 K, 10,138 pm 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.

In vitro potato plantlet development under different polychromatic LED spectra and dynamic illumination

We studied growth of potato plantlets of two cultivars under different constant polychromatic light-emitting diodes (LEDs) and dynamic lighting with the spectrum modifications during growth. Light sources constructed by us were sunbox SB, red-green-blue RGB, and full spectrum FS, red-blue. White luminescent lamps were used as control light. Dynamic lighting was achieved by transferring groups of plantlets from one box to another. Red/green/blue portions in the light sources were (in percents): 39R/39G/22B for SB, 63R/21G/16B for RGB, 74R/8G/18B for FS, and 22R/49G/29B for control. PPFD was set at 45 μmol/m2 s. Morphometric measurements were made 14 and 28 days after planting. Plantlets developed differently from initial stages. Cultivar 'Red Scarlett' appeared to be more susceptible to different lighting than 'Innovator'. Light variations RGB and RGB-SB were the most favorable for plantlet development. This is the first report on the dynamic lighting application for growing potato plantlets.

Prediction accuracy of L- and M-cone based human pupil light models

Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users’ favor or task. One possible application would be to optimize a light spectrum by using the pupil diameter as a parameter to increase the visual acuity. A spectral- and time-dependent pupil model is the key requirement for this aim. We benchmarked in our work selected L- and M-cone based pupil models to find the estimation error in predicting the pupil diameter for chromatic and polychromatic spectra at 100 cd/m2. We report an increased estimation error up to 1.21 mm for 450 nm at 60–300 s exposure time. At short exposure times, the pupil diameter was approximately independent of the used spectrum, allowing to use the luminance for a pupil model. Polychromatic spectra along the Planckian locus showed at 60–300 s exposure time, a prediction error within a tolerance range of ± 0.5 mm. The time dependency seems to be more essential than the spectral dependency when using polychromatic spectra.

Spectra manipulation with the photorefractive effect via the spatial-spectral correspondence relationship.

We propose a scheme based on the photorefractive effect to manipulate polychromatic spectra. A sinusoidal phase grating can be obtained by exposing photorefractive material to light, and it is used to diffract monochromatic or polychromatic light. The resultant diffracted spatial intensity distribution for monochromatic light is mapped to spectrum distribution for polychromatic light via the spatial-spectral correspondence relationship for mono-polychromatic light diffraction. Theoretical analyses and numerical examples show that for different detection angles, the diffracted spectrum exhibits different features, and that specific spectral line selection or line filter effects can be achieved. We also discuss the possibility of applying this spectral scheme to detect temperature or the grating's period changes.

Exploratory research into reduction of scatter and beam hardening in industrial computed tomography using convolutional neural networks

Owing to recent advancements in the field of machine learning, such as deep convolutional neural networks (CNN), new applications in image processing have become feasible. The aim of this study was to explore the use of CNNs for the correction of X-ray scatter and beam hardening in industrial computed tomography. Through simulation, a large heterogeneous set of radiographs was produced, comprising monochromatic and polychromatic X-ray spectra with or without simulated scatter. This data was used to train three CNNs: a single network in which the overall effect of scatter and beam hardening is estimated, as well as a dual network in which both effects are estimated separately (i.e. scatter correction first, followed by beam hardening correction). Application of the trained CNNs on testing data showed superior performance for the dual network, at the cost of a increased training time.

Spectral manipulation and tunable optical frequency ruler using liquid crystal’s birefringence

The polarization control method using a birefringent solid crystal produces only fixed optical frequency rulers and complementary spectra. A configuration using liquid crystal (LC) improves and extends above method’s ability to control incident polychromatic light spectra. It is shown that, by adjusting the voltage applied to the LC module, the induced birefringence and phase shift can be controlled in a wide range; consequently, this scheme can be employed to realize tunable optical frequency ruler, spectral switches, and spectrum compression. Compared with the previous one, this work provides an easier, and more powerful way to manipulate polychromatic light, which benefits its future applications, such as optics communication, spectra control, etc.

Modeling of Nonlocal Thermodynamic Equilibrium Effects in the Classical and Principal Component‐Based Version of the RTTOV Fast Radiative Transfer Model

AbstractThe direct assimilation in 4D‐Var of principal component (PC) scores derived from Infrared Atmospheric Sounding Interferometer (IASI) spectra has recently been demonstrated. To maximize the exploitation of the IASI instrument, a future step is to consider the extension of the PC approach to the extraction of information from the 4.3‐μm CO2‐absorbing region. Shortwave IASI channels are currently underused compared to similar longwave channels because of day‐night variations in data usability due to departures from local thermodynamic equilibrium (LTE). In this paper, we document the introduction of non‐LTE (NLTE) effects in the PC‐based version of the radiative transfer for TIROS operational vertical sounder (RTTOV) fast radiative transfer model (PC‐RTTOV). The inclusion of NLTE effects in PC‐RTTOV has required the development of a parameterized scheme that allows the fast computation of a NLTE correction to LTE radiances. The fast NLTE model is general enough to be applied to any sensor and can be utilized to add a fast and accurate NLTE correction to polychromatic LTE spectra computed by any general radiative transfer model, including RTTOV, which now incorporates the fast NLTE model developed in this study. The accuracy of the NLTE correction is such that daytime and nighttime radiances can be simulated to almost the same degree of accuracy. The comparison with IASI observations shows that the fast NLTE model presented here performs significantly better than the fast NLTE model incorporated in the previous version of RTTOV and also that improvements have to be made to the simulation of NLTE effects at winter high latitudes.

Linear iterative near-field phase retrieval (LIPR) for dual-energy x-ray imaging and material discrimination.

Near-field x-ray refraction (phase) contrast is unavoidable in many lab-based micro-CT imaging systems. Quantitative analysis of x-ray refraction (a.k.a. phase retrieval) is in general an under-constrained problem. Regularizing assumptions may not hold true for interesting samples; popular single-material methods are inappropriate for heterogeneous samples, leading to undesired blurring and/or over-sharpening. In this paper, we constrain and solve the phase-retrieval problem for heterogeneous objects, using the Alvarez-Macovski model for x-ray attenuation. Under this assumption we neglect Rayleigh scattering and pair production, considering only Compton scattering and the photoelectric effect. We formulate and test the resulting method to extract the material properties of density and atomic number from single-distance, dual-energy imaging of both strongly and weakly attenuating multi-material objects with polychromatic x-ray spectra. Simulation and experimental data are used to compare our proposed method with the Paganin single-material phase-retrieval algorithm, and an innovative interpretation of the data-constrained modeling phase-retrieval technique.

SU-E-I-22: Metal Artifact Correction Using KV and Selective MV Imaging.

To improve the image quality of radiotherapy planning CTs for patients with metal implants or fillings by completing the missing kV projection data with selectively acquired MV data that does not suffer from photon starvation. Using both imaging systems that are available on current radiotherapy devices, streaking artifacts are avoided and the soft tissue contrast is restored, even in areas where the kV photons do not contribute any information. This enables a better delineation of structures of interest in planning CT images for patients with metal objects. An algorithm for combining kV and MV projection data from the two on-board imagers of a radiotherapy device is presented in this work. It only requires selective MV imaging with the high energy X-rays being collimated onto the metal implants, ensuring that the patient dose does not increase significantly. The algorithm can cope with non-identical geometries of the two imagers and is based on stitching together kV and MV sinograms by estimating a ratio between them. A numerical head phantom with two dental fillings and two soft tissue patterns was used to quantitatively evaluate the proposed hybrid reconstruction algorithm. A structural similarity index (SSIM) with respect to the ground truth data was computed for two ROIs. Realistic, polychromatic spectra were used for both imagers with 120 keV(p) and 6 MeV(p). The patient dose was limited to about 6 cGy for both acquisitions combined. The reconstruction results yield visually as well as objectively better results (SSIM=74.8%) than a simple sinogram interpolation of the kV data (SSIM=69.7%) or a reconstruction from the original data (SSIM=17.9%). We have successfully implemented a new reconstruction method for hybrid kV-MV cone beam CT reconstruction that enables a better planning of radiotherapy treatments for patients with metal implants without compromising their safety. This work was funded by NIH grant 1R01CA138426-01A1.

Spectral optimization for micro‐CT

To optimize micro-CT protocols with respect to x-ray spectra and thereby reduce radiation dose at unimpaired image quality. Simulations were performed to assess image contrast, noise, and radiation dose for different imaging tasks. The figure of merit used to determine the optimal spectrum was the dose-weighted contrast-to-noise ratio (CNRD). Both optimal photon energy and tube voltage were considered. Three different types of filtration were investigated for polychromatic x-ray spectra: 0.5 mm Al, 3.0 mm Al, and 0.2 mm Cu. Phantoms consisted of water cylinders of 20, 32, and 50 mm in diameter with a central insert of 9 mm which was filled with different contrast materials: an iodine-based contrast medium (CM) to mimic contrast-enhanced (CE) imaging, hydroxyapatite to mimic bone structures, and water with reduced density to mimic soft tissue contrast. Validation measurements were conducted on a commercially available micro-CT scanner using phantoms consisting of water-equivalent plastics. Measurements on a mouse cadaver were performed to assess potential artifacts like beam hardening and to further validate simulation results. The optimal photon energy for CE imaging was found at 34 keV. For bone imaging, optimal energies were 17, 20, and 23 keV for the 20, 32, and 50 mm phantom, respectively. For density differences, optimal energies varied between 18 and 50 keV for the 20 and 50 mm phantom, respectively. For the 32 mm phantom and density differences, CNRD was found to be constant within 2.5% for the energy range of 21-60 keV. For polychromatic spectra and CMs, optimal settings were 50 kV with 0.2 mm Cu filtration, allowing for a dose reduction of 58% compared to the optimal setting for 0.5 mm Al filtration. For bone imaging, optimal tube voltages were below 35 kV. For soft tissue imaging, optimal tube settings strongly depended on phantom size. For 20 mm, low voltages were preferred. For 32 mm, CNRD was found to be almost independent of tube voltage. For 50 mm, voltages larger than 50 kV were preferred. For all three phantom sizes stronger filtration led to notable dose reduction for soft tissue imaging. Validation measurements were found to match simulations well, with deviations being less than 10%. Mouse measurements confirmed simulation results. Optimal photon energies and tube settings strongly depend on both phantom size and imaging task at hand. For in vivo CE imaging and density differences, strong filtration and voltages of 50-65 kV showed good overall results. For soft tissue imaging of animals the size of a rat or larger, voltages higher than 65 kV allow to greatly reduce scan times while maintaining dose efficiency. For imaging of bone structures, usage of only minimum filtration and low tube voltages of 40 kV and below allow exploiting the high contrast of bone at very low energies. Therefore, a combination of two filtrations could prove beneficial for micro-CT: a soft filtration allowing for bone imaging at low voltages, and a variable stronger filtration (e.g., 0.2 mm Cu) for soft tissue and contrast-enhanced imaging.

Estimating Transmission Curves of Primary X-Ray Beams Used in Diagnostic Radiology

This paper shows the comparison among experimental, theoretical published data and data generated by the Geant4 toolkit to determine X-ray transmission curves in an energy range suitable for radiology as well a study of the influence of spectra and shielding composition on transmission data. The objectives of this work were: to compare the differences on transmission data considering different shielding material composition, to validate the application for Geant4 and to calculate transmission curves for new material based on the proposed methodology. Transmission curves and fitting equations for lead, concrete, barited concrete and barited mortar were obtained as a function of shielding thickness and X-ray polychromatic spectra. The simulated transmission curves for lead showed to be statistically the same when compared to published reference. Good agreement was calculated between the experimental data and the data simulated using Geant4. For the other composite materials no comparable reference data is available, but the spread in the transmission values is below 10% for the range of the thicknesses used in real shielding. The results showed that changes in composition for the studied materials can have some impact on the transmission data. The X-ray transmission was sensitive to changes in the incoming beam energy spectra for a fixed acceleration voltage. The simulation application developed in this work can be used, associated to a shielding composition elemental analysis, to customize transmission curves for different composite materials and X-ray spectra.

Bayesian deconvolution as a method for the spectroscopy of X-rays with highly pixelated photon counting detectors

The energy deposition spectrum of highly pixelated photon-counting pixel detectors with a semiconductor sensor layer (e.g. silicon) differs significantly from the impinging X-ray spectrum. This is mainly due to Compton scattering, charge sharing, an energy-dependent sensor efficiency, fluorescence photons and back-scattered photons from detector parts. Therefore, the determination of the impinging X-ray spectrum from the measured distribution of the energy deposition in the detector is a non-trivial task. For the deconvolution of the measured distribution into the impinging spectrum, a set of monoenergetic response functions is needed. Those have been calculated with the Monte Carlo simulation framework ROSI, utilizing EGS4 and including all relevant physical processes in the sensor layer.We have investigated the uncertainties that spectrum reconstructionalgorithms, like spectrum stripping, impose on reconstructionresults. We can show that applying the Bayesian deconvolution methodsignificantly improves the stability of the deconvolved spectrum. Thisresults in a reduced minimum radiation flux needed for reconstruction.In this paper, we present our investigations and measurements onspectrum reconstruction for polychromatic X-ray spectra at low fluxwith a focus on Bayesian deconvolution.