Zhongxing Zhou

Techniques to improve the accuracy of noise power spectrum measurements in digital x‐ray imaging based on background trends removal

PURPOSEnNoise characterization through estimation of the noise power spectrum (NPS) is a central component of the evaluation of digital x-ray systems. Extensive works have been conducted to achieve accurate and precise measurement of NPS. One approach to improve the accuracy of the NPS measurement is to reduce the statistical variance of the NPS results by involving more data samples. However, this method is based on the assumption that the noise in a radiographic image is arising from stochastic processes. In the practical data, the artifactuals always superimpose on the stochastic noise as low-frequency background trends and prevent us from achieving accurate NPS. The purpose of this study was to investigate an appropriate background detrending technique to improve the accuracy of NPS estimation for digital x-ray systems.nnnMETHODSnIn order to achieve the optimal background detrending technique for NPS estimate, four methods for artifactuals removal were quantitatively studied and compared: (1) Subtraction of a low-pass-filtered version of the image, (2) subtraction of a 2-D first-order fit to the image, (3) subtraction of a 2-D second-order polynomial fit to the image, and (4) subtracting two uniform exposure images. In addition, background trend removal was separately applied within original region of interest or its partitioned sub-blocks for all four methods. The performance of background detrending techniques was compared according to the statistical variance of the NPS results and low-frequency systematic rise suppression.nnnRESULTSnAmong four methods, subtraction of a 2-D second-order polynomial fit to the image was most effective in low-frequency systematic rise suppression and variances reduction for NPS estimate according to the authors digital x-ray system. Subtraction of a low-pass-filtered version of the image led to NPS variance increment above low-frequency components because of the side lobe effects of frequency response of the boxcar filtering function. Subtracting two uniform exposure images obtained the worst result on the smoothness of NPS curve, although it was effective in low-frequency systematic rise suppression. Subtraction of a 2-D first-order fit to the image was also identified effective for background detrending, but it was worse than subtraction of a 2-D second-order polynomial fit to the image according to the authors digital x-ray system.nnnCONCLUSIONSnAs a result of this study, the authors verified that it is necessary and feasible to get better NPS estimate by appropriate background trend removal. Subtraction of a 2-D second-order polynomial fit to the image was the most appropriate technique for background detrending without consideration of processing time.

Monotone spline regression for accurate MTF measurement at low frequencies

The modulation transfer function (MTF) of radiographic systems is frequently evaluated by the systems line spread function (LSF) using narrow slits. The conventional slit method requires LSF tail approximation, which is achieved by exponentially extrapolating the LSF tails beyond 1% of peak value. However, the estimated MTF at low frequencies from extrapolation may not reflect the true performance of the system. In this study, a monotone spline regression technique for LSF tail approximation is developed to improve the accuracy of MTF estimation at low frequencies. This technique is based on the underlying physical principles of the system response. The advantages of this technique are demonstrated with simulated examples of which the true MTFs are known. The application of this measurement technique is also demonstrated.

Combined hemoglobin and fluorescence diffuse optical tomography for breast tumor diagnosis: a pilot study on time-domain methodology

A combined time-domain fluorescence and hemoglobin diffuse optical tomography (DOT) system and the image reconstruction methods are proposed for enhancing the reliability of breast-dedicated optical measurement. The system equipped with two pulsed laser diodes at wavelengths of 780 nm and 830 nm that are specific to the peak excitation and emission of the FDA-approved ICG agent, and works with a 4-channel time-correlated single photon counting device to acquire the time-resolved distributions of the light re-emissions at 32 boundary sites of tissues in a tandem serial-to-parallel mode. The simultaneous reconstruction of the two optical (absorption and scattering) and two fluorescent (yield and lifetime) properties are achieved with the respective featured-data algorithms based on the generalized pulse spectrum technique. The performances of the methodology are experimentally assessed on breast-mimicking phantoms for hemoglobin- and fluorescence-DOT alone, as well as for fluorescence-guided hemoglobin-DOT. The results demonstrate the efficacy of improving the accuracy of hemoglobin-DOT based on a priori fluorescence localization.

Shape-parameterized diffuse optical tomography holds promise for sensitivity enhancement of fluorescence molecular tomography.

A fundamental approach to enhancing the sensitivity of the fluorescence molecular tomography (FMT) is to incorporate diffuse optical tomography (DOT) to modify the light propagation modeling. However, the traditional voxel-based DOT has been involving a severely ill-posed inverse problem and cannot retrieve the optical property distributions with the acceptable quantitative accuracy and spatial resolution. Although, with the aid of an anatomical imaging modality, the structural-prior-based DOT method with either the hard- or soft-prior scheme holds promise for in vivo acquiring the optical background of tissues, the low robustness of the hard-prior scheme to the segmentation error and inferior performance of the soft-prior one in the quantitative accuracy limit its further application. We propose in this paper a shape-parameterized DOT method for not only effectively determining the regional optical properties but potentially achieving reasonable structural amelioration, lending itself to FMT for comparably improved recovery of fluorescence distribution.

Application of Fourier-wavelet regularized deconvolution for improving image quality of free space propagation x-ray phase contrast imaging

New x-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source size and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the blurred x-ray phase contrast images. In this study, three different deconvolution techniques, including Wiener filtering, Tikhonov regularization and Fourier-wavelet regularized deconvolution (ForWaRD), were applied to the simulated and experimental free space propagation x-ray phase contrast images of simple geometric phantoms. These algorithms were evaluated in terms of phase contrast improvement and signal-to-noise ratio. The results demonstrate that the ForWaRD algorithm is most appropriate for phase contrast image restoration among above-mentioned methods; it can effectively restore the lost information of phase contrast fringes while reduce the amplified noise during Fourier regularization.

Combined diffuse optical tomography and photoacoustic tomography for enhanced functional imaging of small animals: a methodological study on phantoms.

Hybrid imaging methods combining diffuse optical tomography (DOT) and other anatomical or nonoptical functional modalities have been widely investigated to improve imaging performance degraded by the strong optical scattering of biological tissues, through constraining the reconstruction process by prior structures. However, these modalities with different contrast mechanisms may be ineffective in revealing early-staged lesions with high optical contrast but no morphological changes. Photoacoustic tomography (PAT) is particularly useful for visualizing light-absorbing structures embedded in soft tissues with high spatial resolution. Although it is still challenging for PAT to quantitatively disclose the absorption distribution, the modality does provide reliable and specific a priori information differentiating light-absorbing structures of soft tissues and might be more appropriate to guide DOT in lesion diagnosis, as compared with other anatomical or nonoptical functional modalities. In this study, a PAT-guided DOT approach is introduced with both soft- and hard-prior regularizations. The methodology is experimentally validated on small-animal-sized phantoms using a computed-tomography-analogous (CT-analogous) PAT/DOT dual-modality system, focusing on future whole-body applications. The results show that the proposed scheme is capable of effectively improving the quantitative accuracy and spatial resolution of DOT reconstruction.

Improving the accuracy of MTF measurement at low frequencies based on oversampled edge spread function deconvolution

The modulation transfer function (MTF) of a radiographic system is often evaluated by measuring the systems edge spread function (ESF) using edge device. However, the numerical differentiation procedure of the traditional slanted edge method amplifies noises in the line spread function (LSF) and limits the accuracy of the MTF measurement at low frequencies. The purpose of this study is to improve the accuracy of low-frequency MTF measurement for digital x-ray imaging systems. An edge spread function (ESF) deconvolution technique was developed for MTF measurement based on the degradation model of slanted edge images. Specifically, symmetric oversampled ESFs were constructed by subtracting a shifted version of the ESF from the original one. For validation, the proposed MTF technique was compared with conventional slanted edge method through computer simulations as well as experiments on two digital radiography systems. The simulation results show that the average errors of the proposed ESF deconvolution technique were 0.11% ± 0.09% and 0.23% ± 0.14%, and they outperformed the conventional edge method (0.64% ± 0.57% and 1.04% ± 0.82% respectively) at low-frequencies. On the experimental edge images, the proposed technique achieved better uncertainty performance than the conventional method. As a result, both computer simulation and experiments have demonstrated that the accuracy of MTF measurement at low frequencies can be improved by using the proposed ESF deconvolution technique.

A CT-analogous scheme for time-domain diffuse fluorescence tomography

A fiber-based non-contact scheme of the time-domain diffuse fluorescence yield and lifetime tomography is described that combines the time-correlated single photon counting technique for high-sensitive, time-resolved detection and CT-analogous configuration for large data-set collection. A pilot validation of the methodology is performed for two-dimensional scenarios using simulated and experimental data. The results demonstrated the efficacy of the proposed scheme in improving the image quality.

Towards pH-sensitive imaging of small animals with photon-counting difference diffuse fluorescence tomography.

Abstract. The importance of cellular pH has been shown clearly in the study of cell activity, pathological feature, and drug metabolism. Monitoring pH changes of living cells and imaging the regions with abnormal pH-values, in vivo, could provide invaluable physiological and pathological information for the research of the cell biology, pharmacokinetics, diagnostics, and therapeutics of certain diseases such as cancer. Naturally, pH-sensitive fluorescence imaging of bulk tissues has been attracting great attentions from the realm of near infrared diffuse fluorescence tomography (DFT). Herein, the feasibility of quantifying pH-induced fluorescence changes in turbid medium is investigated using a continuous-wave difference-DFT technique that is based on the specifically designed computed tomography-analogous photon counting system and the Born normalized difference image reconstruction scheme. We have validated the methodology using two-dimensional imaging experiments on a small-animal-sized phantom, embedding an inclusion with varying pH-values. The results show that the proposed approach can accurately localize the target with a quantitative resolution to pH-sensitive variation of the fluorescent yield, and might provide a promising alternative method of pH-sensitive fluorescence imaging in addition to the fluorescence-lifetime imaging.

An L p (0 ≤ p ≤ 1)-norm regularized image reconstruction scheme for breast DOT with non-negative-constraint

BackgroundIn diffuse optical tomography (DOT), the image reconstruction is often an ill-posed inverse problem, which is even more severe for breast DOT since there are considerably increasing unknowns to reconstruct with regard to the achievable number of measurements. One common way to address this ill-posedness is to introduce various regularization methods. There has been extensive research regarding constructing and optimizing objective functions. However, although these algorithms dramatically improved reconstruction images, few of them have designed an essentially differentiable objective function whose full gradient is easy to obtain to accelerate the optimization process.MethodsThis paper introduces a new kind of non-negative prior information, designing differentiable objective functions for cases of L1-norm, Lp (0xa0<xa0pxa0<xa01)-norm and L0-norm. Incorporating this non-negative prior information, it is easy to obtain the gradient of these differentiable objective functions, which is useful to guide the optimization process.ResultsPerformance analyses are conducted using both numerical and phantom experiments. In terms of spatial resolution, quantitativeness, gray resolution and execution time, the proposed methods perform better than the conventional regularization methods without this non-negative prior information.Conclusions The proposed methods improves the reconstruction images using the introduced non-negative prior information. Furthermore, the non-negative constraint facilitates the gradient computation, accelerating the minimization of the objective functions.