In-line X-ray phase contrast imaging (IL-PCI) is a promising technology for clinical diagnosis because of its great advantage in distinguishing low contrast tissues and simple structure to implement. In order to recover the phase projections from the phase contrast measurements, conventional phase retrieval methods were developed based on assumptions such as homogeneous material, weak attenuation, and thus suffered from limited generalizability, practicability and feasibility. Deep learning-based methods have been proposed for phase retrieval and great success has been achieved. While the practical physical model of phase contrast imaging hasn’t been fully considered including the non-ideal effects of finite size of the x-ray micro focal spot, finite pixel size of the detector and the system noise. In this paper, a convolutional network based on generative adversarial network is proposed to retrieve the phase projections with fully considering the non-ideal effects in IL-PCI. The network composed of a generating network from which the phase projections were retrieved and a discriminating network from which the difference between the output of generation network and the reference phase projection is processed and backpropagated to the input of the network. Phase contrast measurements of the microspheres phantom were simulated and retrieved by the conventional methods and the proposed network. Results show the superiority of the proposed network in spatial resolution and noise suppression compared with the conventional method.
Fluorescence pharmacokinetics can analyze the absorption, distribution, metabolism and other pharmacokinetic processes of fluorescence agents in biological tissues over time, which can provide more specific and quantitative physiological and pathological information for the evaluation of organ function. This paper is devoted to studying pharmacokinetics of indocyanine green (ICG) in healthy mice and mice with acute alcoholic liver injury based on a home-made dynamic diffuse fluorescence tomography system that possesses high sensitivity and large dynamic measurement range on account of digital lock-in-photon-counting technique. In this study, four-week-old Kunming mice were randomly divided into experimental and control groups. The time-varying distribution of ICG in mice was obtained by diffuse fluorescence tomography reconstruction, and the pharmacokinetic parameters were further extracted from the ICG concentration-time curve. The results showed that the dynamic diffuse fluorescence tomography system successfully captured the ICG metabolism process in mouse liver, and the ICG excretion rate demonstrated an obvious difference between healthy mice and the mice with acute alcoholic liver injury.
Diffuse Optical Tomography (DOT) is a promising non-invasive optical imaging technology that can provide structural and functional information of biological tissues. Since the diffused light undergoes multiple scattering in biological tissues, and the boundary measurements are limited, the reverse problem of DOT is ill-posed and ill-conditioned. In order to overcome these limitations, two types of neural networks, back-propagation neural network (BPNN) and stacked autoencoder (SAE) were applied in DOT image reconstruction, which use the internal optical properties distribution and the boundary measurement of biological tissues as the input and output data sets respectively to adjust the neural network parameters, and directly establish a nonlinear mapping of the input and output. To verify the effectiveness of the methods, a series of numerical simulation experiments were conducted, and the experimental results were quantitatively assessed, which demonstrated that both methods can accurately predict the position and size of the inclusion, especially in the case of higher absorption contrast. As a whole, SAE can get better reconstructed image results than BPNN and the training time was only a quarter of BPNN.
Pharmacokinetic diffuse fluorescence tomography (DFT) can provide helpful diagnostic information for tumor differentiation and monitoring. Among the methods of achieving pharmacokinetic parameters, adaptive extended Kalman filtering (AEKF) as a nonlinear filter method demonstrates the merits of quantitativeness, noise-robustness, and initialization independence. In this paper, indirect and direct AEKF schemes based on a commonly used two-compartment model were studied to extract pharmacokinetic parameters from simulation data. To assess the effect of metabolic rate on the reconstruction results, a series of numerical simulation experiments with the metabolic time range from 4.16 min to 38 min were carried out and the results obtained by the two schemes were compared. The results demonstrate that when the metabolic time is longer than 18 min, the pharmacokinetic-rate estimates of two schemes are similar; however, when the metabolic time is shorter than 5 min, the pharmacokinetic parameters obtained by the indirect scheme are far from the true value and even unavailable.
X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality which has the potential for achieving both high sensitivity and spatial resolution simultaneously. For the narrow x-ray beam-based XLCT imaging, based on previous work, a spatial resolution of about double the x-ray beam size can be achieved using a translate/rotate scanning scheme, taking step sizes equal to the x-ray beam width. To break the current spatial resolution limit, we propose a scanning strategy achieved by reducing the scanning step size to be smaller than the x-ray beam size. We performed four sets of numerical simulations and a phantom experiment using cylindrical phantoms and have demonstrated that our proposed scanning method can greatly improve the XLCT-reconstructed image quality compared with the traditional scanning approach. In our simulations, by using a fixed x-ray beam size of 0.8 mm, we were able to successfully reconstruct six embedded targets as small as 0.5 mm in diameter and with the same edge-to-edge distances by using a scanning step as small as 0.2 mm which is a 1.6 times improvement in the spatial resolution compared with the traditional approach. Lastly, the phantom experiment further demonstrated the efficacy of our proposed method in improving the XLCT image quality, with all image quality metrics improving as the step size decreased.
Diffuse optical tomography (DOT) is a novel functional imaging technique that has the vital clinical application. Aiming at the problems in DOT technology, we developed a three-wavelength continuous wave DOT system with high sensitivity and temporal resolution by adopting photo-multiple tube and photon counting detection, as well as lock-in technique. To assess the performance of the system, we conducted a series of cylindrical phantom experiments with optical properties that closely match those of human tissue, and obtained the reconstruction images by combining with our developed imaging scheme. The experimental results show that the position and size of the reconstructed targets are accurate, demonstrating the feasibility of the system. Additionally, the sensitivity, quantitativeness and spatial resolution of the imaging system were assessed by varying the target-to-background contrasting absorption contrast and target size. These preliminary results indicate that the system is scientifically capable of subcentimeter resolution imaging of low-contrast the lesion from the normal background.
The purpose of this work is to introduce and study a novel x-ray beam irradiation pattern for X-ray Luminescence Computed Tomography (XLCT), termed multiple intensity-weighted narrow-beam irradiation. The proposed XLCT imaging method is studied through simulations of x-ray and diffuse lights propagation. The emitted optical photons from X-ray excitable nanophosphors were collected by optical fiber bundles from the right-side surface of the phantom. The implementation of image reconstruction is based on the simulated measurements from 6 or 12 angular projections in terms of 3 or 5 x-ray beams scanning mode. The proposed XLCT imaging method is compared against the constant intensity weighted narrow-beam XLCT. From the reconstructed XLCT images, we found that the Dice similarity and quantitative ratio of targets have a certain degree of improvement. The results demonstrated that the proposed method can offer simultaneously high image quality and fast image acquisition.
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.
Phase contrast x-ray imaging techniques have shown the ability to overcome the weakness of the low sensitivity of conventional x-ray imaging. Among them, in-line phase contrast imaging, blessed with simplicity of arrangement, is deemed to be a promising technique in clinical application. To obtain quantitative information from in-line phase contrast images, numerous phase-retrieval techniques have been developed. The theories of these phase-retrieval techniques are mostly proposed on the basis of the ideal detector and the noise-free environment. However, in practice, both detector resolution and system noise would have impacts on the performance of these phase-retrieval methods. To assess the impacts of above-mentioned factors, we include the effects of Gaussian shaped detectors varying in the full width at half maximum (FWHM) and system noise at different levels into numerical simulations. The performance of the phase-retrieval methods under such conditions is evaluated by the root mean square error. The results demonstrate that an increase in the detector FWHM or noise level degrades the effect of phase retrieval, especially for objects in small size.
X-ray phase contrast imaging (XPCI) is a novel method that exploits the phase shift for the incident X-ray to form an image. Various XPCI methods have been proposed, among which, in-line phase contrast imaging (IL-PCI) is regarded as one of the most promising clinical methods. The contrast of the interface is enhanced due to the introduction of the boundary fringes in XPCI, thus it is generally used to evaluate the image quality of XPCI. But the contrast is a comprehensive index and it does not reflect the information of image quality in the frequency range. The modulation transfer function (MTF), which is the Fourier transform of the system point spread function, is recognized as the metric to characterize the spatial response of conventional X-ray imaging system. In this work, MTF is introduced into the image quality evaluation of the IL-PCI system. Numerous simulations based on Fresnel - Kirchhoff diffraction theory are performed with varying system settings and the corresponding MTFs were calculated for comparison. The results show that MTF can provide more comprehensive information of image quality comparing to contrast in IL-PCI.
There is a direct evidence that the radiation doses associated with CT scans are associated with an increase in cancer risk. To reduce the radiation dose and simultaneously maintain the CT reconstruction quality, numerous algorithms have been proposed such as compressive sensing (CS) technique. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use. In this study, we mainly consider the relationship between the CT reconstruction quality and two undersampled scan types of CS technique, i.e., the sparse-view scan and limited-view scan. The results demonstrate that an appropriate selection of scan type of CS technique can effectively control the radiation dose.
In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.
KEYWORDS: Fluorescence tomography, Data modeling, Tissues, Signal to noise ratio, Instrument modeling, Performance modeling, In vivo imaging, Digital filtering, Image filtering, Electronic filtering
We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.
To evaluate the spatial resolution performance of cone beam computed tomography (CBCT) system, accurate measurement of the modulation transfer function (MTF) is required. This accuracy depends on the MTF measurement method and CBCT reconstruction algorithms. In this work, the accuracy of MTF measurement of CBCT system using wire phantom is validated by Monte Carlo simulation. A Monte Carlo simulation software tool BEAMnrc/EGSnrc was employed to model X-ray radiation beams and transport. Tungsten wires were simulated with different diameters and radial distances from the axis of rotation. We adopted filtered back projection technique to reconstruct images from 360° acquisition. The MTFs for four reconstruction kernels were measured from corresponding reconstructed wire images, while the ram-lak kernel increased the MTF relative to the cosine, hamming and hann kernel. The results demonstrated that the MTF degraded radially from the axis of rotation. This study suggested that an increase in the MTF for the CBCT system is possible by optimizing scanning settings and reconstruction parameters.
The modulation transfer function (MTF) is widely used to describe the spatial resolution of x-ray imaging systems.
Extensive works have been conducted to achieve accurate and precise measurement of MTF by using a slanted edge test
device. The noise level of the slanted edge image is an important factor influencing the accuracy of MTF measurement.
Thus in this work, a comparison study was made on the MTF measurement results obtained by using different curve
fitting algorithms for ESF determination when analyzing the same image data with different noise levels. The results
indicated that the averaged MTF measurement errors got increased with the decrease of the signal-to-noise ratio of the
slanted edge images for all of the ESF processing algorithms. But for the same noisy slanted edge image, monotonic
fitting algorithm outperformed Gaussian smoothing method or moving polynominal fitting method on MTF
measurement.
We developed a novel method for determining the presampling modulation transfer function (MTF) of digital radiography systems from slanted edge images based on Wiener deconvolution. The degraded supersampled edge spread function (ESF) was obtained from simulated slanted edge images with known MTF in the presence of poisson noise, and its corresponding ideal ESF without degration was constructed according to its central edge position. To meet the requirements of the absolute integrable condition of Fourier transformation, the origianl ESFs were mirrored to construct the symmetric pattern of ESFs. Then based on Wiener deconvolution technique, the supersampled line spread function (LSF) could be acquired from the symmetric pattern of degraded supersampled ESFs in the presence of ideal symmetric ESFs and system noise. The MTF is then the normalized magnitude of the Fourier transform of the LSF. The determined MTF showed a strong agreement with the theoritical true MTF when appropriated Wiener parameter was chosen. The effects of Wiener parameter value and the width of square-like wave peak in symmetric ESFs were illustrated and discussed. In conclusion, an accurate and simple method to measure the presampling MTF was established using Wiener deconvolution technique according to slanted edge images.
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.
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 high throughput data collection. A pilot validation of the methodology is performed for
two-dimensional scenarios using simulated and experimental data. The results demonstrated the potential of the proposed
scheme in improving the image quality.
New X-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the
negative effects of finite source sizes 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 x-ray phase contrast images. In this study, four different deconvolution techniques were applied to
experimental phase contrast images of a simple geometric phantom, including Weiner deconvolution method and
Tikhonov regularization techniques with their Tikhonov matrix separately set as identity matrix, first order difference
operator and second order difference operator. According to the free space propagation x-ray phase contrast imaging
system, the source-to-sample distance (SS) of 200cm or 180cm was used with corresponding sample-to-detector distance
(SD) of 20cm or 40cm. Image contrasts of 9.8%, 52.7%, 27.6% and 31.5% were separately obtained corresponding to
above mentioned four techniques with SS/SD=200cm/20cm. For the second system setting (SS/SD=180cm/40cm),
image contrasts of 11.9%, 112.8%, 66.3% and 76.5% were obtained separately. The Tikhonov regularization technique
with Tikhonov matrix chosen as identity matrix obtains the highest contrast among all techniques. However, under this
case, most noticeable artifacts and noise were introduced simultaneously. With full consideration on noise and artifacts,
the Tikhonov matrix of second order difference operator will be the best choice for Tikhonov regularization method.
A prototype time-domain fluorescence diffusion optical tomography (FDOT) system using near-infrared light is
presented. The system employs two pulsed light sources, 32 source fibers and 32 detection channels, working separately
for acquiring the temporal distribution of the photon flux on the tissue surface. The light sources are provided by low
power picosecond pulsed diode lasers at wavelengths of 780 nm and 830 nm, and a 1×32-fiber-optic-switch sequentially
directs light sources to the object surface through 32 source fibers. The light signals re-emitted from the object are
collected by 32 detection fibers connected to four 8×1 fiber-optic-switch and then routed to four time-resolved
measuring channels, each of which consists of a collimator, a filter wheel, a photomultiplier tube (PMT)
photon-counting head and a time-correlated single photon counting (TCSPC) channel. The performance and efficacy of
the designed multi-channel PMT-TCSPC system are assessed by reconstructing the fluorescent yield and lifetime
images of a solid phantom.
Noise 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.
However, this method is based on the assumption that the noise in a radiographic image is arising from stochastic
(random) 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. In this study, NPS measurement was implemented and
compared before and after background trends removal, the results showed that background detrending reduced the
variance of the low-frequency spectral components, hence improving the accuracy of NPS measurement. Our results also
showed that involving more samples for ensemble averaging had little effect in reducing the variance of the low-frequency
spectral components. All results implied that it is necessary and feasible to get better NPS estimate by
appropriate background detredning.
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