Objective.In this work, we aim to propose an accurate and robust spectrum estimation method by synergistically combining x-ray imaging physics with a convolutional neural network (CNN).Approach.The approach relies on transmission measurements, and the estimated spectrum is formulated as a convolutional summation of a few model spectra generated using Monte Carlo simulation. The difference between the actual and estimated projections is utilized as the loss function to train the network. We contrasted this approach with the weighted sums of model spectra approach previously proposed. Comprehensive studies were performed to demonstrate the robustness and accuracy of the proposed approach in various scenarios.Main results.The results show the desirable accuracy of the CNN-based method for spectrum estimation. The ME and NRMSE were -0.021 keV and 3.04% for 80 kVp, and 0.006 keV and 4.44% for 100 kVp, superior to the previous approach. The robustness test and experimental study also demonstrated superior performances. The CNN-based approach yielded remarkably consistent results in phantoms with various material combinations, and the CNN-based approach was robust concerning spectrum generators and calibration phantoms.Significance. We proposed a method for estimating the real spectrum by integrating a deep learning model with real imaging physics. The results demonstrated that this method was accurate and robust in estimating the spectrum, and it is potentially helpful for broad x-ray imaging tasks.

This study presents a measurement principle for determining the size of the ablation zone in MWA, which could ultimately form an alternative to more expensive monitoring approaches like CT. The measurement method is based on a microwave transmission measurement. A MWA is performed experimentally on ex vivo bovine liver to determine the ablation zone. This setup uses a custom slot applicator performing the MWA at an operating frequency of 2.45 GHz and a custom bowtie antenna measuring the waves transmitted from the applicator. Furthermore, a custom measurement probe is used to determine the dielectric properties. A time-shift analysis is used to determine the radial extent of the ablation zone. Several measurements are carried out with a power of 50 W for 10 min to show the reproducibility. The results show that this method can provide reproducible outcomes to determine the ablation zone with a maximum error of 4.11%.

UNASSIGNED: The energy spectrum is the property of the X-ray tube that describes the energy fluence per unit interval of photon energy. The existing indirect methods for estimating the spectrum ignore the influence caused by the voltage fluctuation of the X-ray tube.
UNASSIGNED: In this work, we propose a method for estimating the X-ray energy spectrum more accurately by including the voltage fluctuation of the X-ray tube. It expresses the spectrum as the weighted summation of a set of model spectra within a certain voltage fluctuation range. The difference between the raw projection and the estimated projection is considered as the objective function for obtaining the corresponding weight of each model spectrum. The equilibrium optimizer (EO) algorithm is used to find the weight combination that minimizes the objective function. Finally, the estimated spectrum is obtained. We refer to the proposed method as the poly-voltage method. The method is mainly aimed at the cone-beam computed tomography (CBCT) system.
UNASSIGNED: The model spectra mixture evaluation and projection evaluation showed that the reference spectrum can be combined by multiple model spectra. They also showed that it is appropriate to choose about 10% of the preset voltage as the voltage range of the model spectra, which can match the reference spectrum and projection quite well. The phantom evaluation showed that the beam-hardening artifact can be corrected using the estimated spectrum via the poly-voltage method, and the poly-voltage method provides not only the accurate reprojection but also an accurate spectrum. The normalized root mean square error (NRMSE) index between the spectrum generated via the poly-voltage method and the reference spectrum could be kept within 3% according to above evaluations. There existed a 1.77% percentage error between the estimated scatter of polymethyl methacrylate (PMMA) phantom using the two spectra generated via the poly-voltage method and the single-voltage method, and it could be considered for scatter simulation.
UNASSIGNED: Our proposed poly-voltage method could estimate the spectrum more accurately for both ideal and more realistic voltage spectra, and it is robust to the different modes of voltage pulse.

OBJECTIVE: Conventional x-ray spectrum estimation methods from transmission measurement often lead to inaccurate results when extensive x-ray scatter is present in the measured projection. This study aims to apply the weighted L1-norm scatter correction algorithm in spectrum estimation for reducing residual differences between the estimated and true spectrum.
METHODS: The scatter correction algorithm is based on a simple radiographic scattering model where the intensity of scattered x-ray is directly estimated from a transmission measurement. Then, the scatter-corrected measurement is used for the spectrum estimation method that consists of deciding the weights of predefined spectra and representing the spectrum as a linear combination of the predefined spectra with the weights. The performances of the estimation method combined with scatter correction are evaluated on both simulated and experimental data.
RESULTS: The results show that the estimated spectra using the scatter-corrected projection nearly match the true spectra. The normalized-root-mean-square-error and the mean energy difference between the estimated spectra and corresponding true spectra are reduced from 5.8% and 1.33 keV without the scatter correction to 3.2% and 0.73 keV with the scatter correction for both simulation and experimental data, respectively.
CONCLUSIONS: The proposed method is more accurate for the acquisition of x-ray spectrum than the estimation method without scatter correction and the spectrum can be successfully estimated even the materials of the filters and their thicknesses are unknown. The proposed method has the potential to be used in several diagnostic x-ray imaging applications.

OBJECTIVE: The complex beam delivery techniques for patient treatment using a clinical linear accelerator (linac) may result in variations in the photon spectra, which can lead to dosimetric differences in patients that cannot be accounted for by current treatment planning systems (TPSs). Therefore, precise knowledge of the fluence and energy spectrum (ES) of the therapeutic beam is very important. However, owing to the high energy and flux of the beam, the ES cannot be measured directly, and validation of the spectrum modeled in the TPS is difficult. The aim of this study is to develop an efficient beam transmission measurement procedure for accurately reconstructing the ES of a therapeutic x-ray beam generated by a clinical linac.
METHODS: The attenuation of a 6 MV photon beam from an Elekta Synergy Platform clinical linac through different thicknesses of graphite and lead was measured using an ion chamber. The response of the ion chamber as a function of photon energy was obtained using the Monte Carlo (MC) method in the Geant4 simulation code. Using the curves obtained in the photon beam transmission measurements and the ion chamber energy response, the ES was reconstructed using an iterative algorithm based on a mathematical model of the spectrum. To evaluate the accuracy of the spectrum reconstruction method, the reconstructed ES (ESrecon ) was compared to that determined by the MC simulation (ESMC ).
RESULTS: The ion chamber model in the Geant4 simulation was well validated by comparing the ion chamber perturbation factors determined by the TRS-398 calibration protocol and EGSnrc; the differences were within 0.57%. The number of transmission measurements was optimized to 10 for efficient spectrum reconstruction according to the rate of increase in the spectrum reconstruction accuracy. The distribution of ESrecon obtained using the measured transmission curves was clearly similar to the reference, ESMC , and the dose distributions in water calculated using ESrecon and ESMC were similar within a 2% local difference. However, in a heterogeneous medium, the dose discrepancy between them was >5% when a complex beam delivery technique composed of 171 control points was used.
CONCLUSIONS: The proposed measurement procedure required a total time of approximately 1 h to obtain and analyze 20 transmission measurements. In addition, it was confirmed that the transmission curve of high-Z materials influences the accuracy of spectrum reconstruction more than that of low-Z materials. A well-designed transmission measurement protocol suitable for clinical environments could be an essential tool for better dosimetric accuracy in patient treatment and for periodic verification of the beam quality.

Transmission measurement has been perceived as a potential candidate for label-free investigation of biological material. It is a real-time, label-free and non-invasive optical detection technique that has found wide applications in pharmaceutical industry as well as the biological and medical fields. Combining transmission measurement with optical trapping has emerged as a powerful tool allowing stable sample trapping, while also facilitating transmittance data analysis. In this study, a near-infrared laser beam emitting at a wavelength of 1064 nm was used for both optical trapping and transmission measurement investigation of human immunodeficiency virus 1 (HIV-1) infected and uninfected TZM-bl cells. The measurements of the transmittance intensity of individual cells in solution were carried out using a home built optical trapping system combined with laser transmission setup using a single beam gradient trap. Transmittance spectral intensity patterns revealed significant differences between the HIV-1 infected and uninfected cells. This result suggests that the transmittance data analysis technique used in this study has the potential to differentiate between infected and uninfected TZM-bl cells without the use of labels. The results obtained in this study could pave a way into developing an HIV-1 label-free diagnostic tool with possible applications at the point of care .

As one of the most advanced non-destructive analytical techniques for nuclear wastes, tomographic Gamma Scanning (TGS) is able to give accurate quantitative and qualitative measurements of nuclear waste barrels. OSEM (Ordered Subsets Expectation Maximization) has been used in transmission TGS image reconstruction on account of its good reconstruction quality and ideal convergence rate. In this paper, an improved method-NMO-OSEM (Non-minimization optimization OSEM) was proposed, it\'s an iterative algorithm with corrected initial values optimized by non-minimization optimization method. To evaluate its performance, a TGS system is used to perform transmission measurements on barreled nuclear wastes. The results show: ①Compared with the reconstructed images by traditional OSEM under 6 transmission energies (122 keV, 344 keV, 779 keV, 964 keV, 1112 keV, 1408 keV), the improved NMO-OSEM has a great advantage in reducing the artifacts and effectively improving the quality of the reconstructed images. ②the attenuation coefficients values of 72 voxels under 3 emission energies (662 keV, 1173 keV and 1332 keV) reconstructed by the proposed algorithm are more accurate (range of error: 0.22%-13.83%) than reconstructed by traditional OSEM (range of error: 1.31%-32.21%), which proves this method has more stable reconstruction precision and could be regarded as an ideal option for real applications.

Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range.

OBJECTIVE: Former studies have shown that in homogeneities in the path of therapeutic proton beams can lead to a degradation of the distal edge of the Bragg peak. These studies mostly investigated bone-air interfaces. This study focuses on distal edge degradation caused by finely structured soft tissue - air interfaces, which can be found in lung tissue.
METHODS: A randomly filled voxelized lung-like phantom was designed and produced using rapid prototyping methods. The results of transmission measurements on this phantom were used to validate Monte Carlo (MC) calculations, which were then used as gold standard to calculate doses in several lung equivalent geometries (phantoms). The results were compared to the results of analytical dose calculation engines.
RESULTS: Transmission measurements showed that the distal falloff width (from 90 % of the peak dose to 10 %) in water increased from 3.32 mm by 117 % to 7.19 mm for an initial proton energy of 140 MeV, and from 5.95 mm to 9.03 mm (52 %) for 200 MeV. The peak dose in the degraded beam was only 70 % (for 140 MeV) and 84 % (for 200 MeV) of the value observed in non-degraded beams. These findings were in contrast to the results obtained with analytical dose computation engines, but are in agreement with MC calculations.
CONCLUSIONS: If not predicted correctly, Distal Edge Degradation in lung cancer therapy can lead to severe under-dosage of the target region and unwanted dose in organs at risk distal to the Bragg peak. Therefore clinically used dose calculation algorithms have to be extended to take lateral in homogeneities into account.

OBJECTIVE: To demonstrate the application of in-vivo diffuse optical transmission spectroscopy in quantifying oxygen saturation in interstitial tissue, and to use this technique to examine reoxygenation dynamics in real-time as tumors responds to radiotherapy.
METHODS: Two 200 micron core fiber optics were threaded through two 21 gauge hypodermic needles: one coupled to an OceanOptics QE65000 spectrometer, and the other to an Ocean Optics HL-2000-HP 20W light source. These needles were fixed approximately 3 mm apart, and inserted into nude mice with human head- and-neck tumor xenografts. The oxygen saturation was then measured as a function of time after irradiation at intervals of 0.5, 1, 2, 6, 12, and 24, to measure the tumors\' prompt oxygen saturation response to radiation.
RESULTS: Blood volume, deoxy and oxy-hemoglobin concentrations were measured through least-squares fitting of transmission spectra. Furthermore, various configurations of interstitial fiber optic probes were explored to optimize signal strength. Improvement of the optical coupling to the biological system and a concurrent increase in source intensity are the main two focuses for boosting signal strength.
CONCLUSIONS: This work has the potential to give an understanding of the time-scales of hypoxia and reoxygenation in vivo as tumors respond to radiation injury. This technique is of particular interest for hypofractionated therapies particularly treatments of only two or three treatments, where optimizing treatment timing can increase the tumorcidal effect of the remaining fractions.