Improved Imaging Performance Research Articles

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

Laboratory demonstration of a cryogenic deformable mirror for wavefront correction of space-borne infrared telescopes.

This paper demonstrates a cryogenic deformable mirror (DM) with 1020 actuators based on micro-electrical mechanical systems (MEMS) technology. Cryogenic space-borne infrared telescopes can experience a wavefront error due to a figure error of their mirror surface, which makes the imaging performance worse. For on-orbit wavefront correction as one solution, we developed a MEMS-processed electro-static DM with a special surrounding structure for use under the cryogenic temperature. We conducted a laboratory demonstration of its operation in three cooling cycles between 5 K and 295 K. Using a laser interferometer, we detected the deformation corresponding to the applied voltages under the cryogenic temperature for the first time. The relationship between voltages and displacements was qualitatively expressed by the quadratic function, which is assumed based on the principle of electro-static DMs. We also found that it had a high operating repeatability of a few nm root-mean-square and no significant hysteresis. Using the measured values of repeatability, we simulated the improvement of the point spread function (PSF) by wavefront correction with our DM. These results show that our developed DM is effective in improving imaging performance and PSF contrast of space-borne infrared telescopes.

Spatial coding in sonar imaging

A practical deployment is presented for sonar imaging with fewer transmitters and receivers. Spatial coding via transmit beamforming is used for target detection and localisation. Transmit beamforming reduces the ambiguity in a model and improves imaging performance. To reconstruct the resultant underdetermined system of equations, a sparse signal reconstruction framework is used, and the inverse problem is solved by using an iterative optimisation algorithm. Deployment is optimised for better target detection and localisation performance. Successful sonar imaging reconstruction is guaranteed by the restricted isometry property with high probability. A numerical simulation shows that the proposed method can detect and localise targets efficiently, with better imaging results than those attained by conventional methods or the compressive sensing method without spatial coding.

Extended Chirp Scaling-Baseband Azimuth Scaling-Based Azimuth–Range Decouple $L_{1}$ Regularization for TOPS SAR Imaging via CAMP

This paper proposes a novel azimuth–range decouple-based $L_{1}$ regularization imaging approach for the focusing in terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR). Since conventional $L_{1}$ regularization technique requires transferring the (2-D) echo data into a vector and reconstructing the scene via 2-D matrix operations leading to significantly more computational complexity, it is very difficult to apply in high-resolution and wide-swath SAR imaging, e.g., TOPS. The proposed method can achieve azimuth–range decouple by constructing an approximated observation operator to simulate the raw data, the inverse of matching filtering (MF) procedure, which makes large-scale sparse reconstruction, or called compressive sensing reconstruction of surveillance region with full- or downsampled raw data in TOPS SAR possible. Compared with MF algorithm, e.g., extended chirp scaling-baseband azimuth scaling, it shows huge potential in image performance improvement; while compared with conventional $L_{1}$ regularization technique, it significantly reduces the computational cost, and provides similar image features. Furthermore, this novel approach can also obtain a nonsparse estimation of considered scene retaining a similar background statistical distribution as the MF-based image, which can be used to the further application of SAR images with precondition being preserving image statistical properties, e.g., constant false alarm rate detection. Experimental results along with a performance analysis validate the proposed method.

$L_{1}$ -Regularization-Based SAR Imaging and CFAR Detection via Complex Approximated Message Passing

Synthetic aperture radar (SAR) is a widely used active high-resolution microwave imaging technique that has all-time and all-weather reconnaissance ability. Compared with traditionally matched filtering (MF)-based methods, ${L_{q}}({0 \le q \le 1})$ regularization technique can efficiently improve SAR imaging performance e.g., suppressing sidelobes and clutter. However, conventional $L_{q}$ -regularization-based SAR imaging approach requires transferring the 2-D echo data into a vector and reconstructing the scene via 2-D matrix operations. This leads to significantly more computational complexity compared with MF, and makes it very difficult to apply in high-resolution and wide-swath imaging. Typical $L_{q}$ regularization recovery algorithms, e.g., iterative thresholding algorithm, can improve imaging performance of bright targets, but not preserve the image background distribution well. Thus, image background statistical-property-based applications, such as constant false alarm rate (CFAR) detection, cannot be applied to regularization recovered SAR images. On the other hand, complex approximated message passing (CAMP), an iterative recovery algorithm for $L_{1}$ regularization reconstruction, can achieve not only the sparse estimation of the original signal as typical regularization recovery algorithms but also a nonsparse solution simultaneously. In this paper, two novel CAMP-based SAR imaging algorithms are proposed for raw data and complex radar image data, respectively, along with CFAR detection via the CAMP recovered nonsparse result. The proposed method for raw data can not only improve SAR image performance as conventional $L_{1}$ regularization technique but also reduce the computational cost efficiently. While only when we have MF recovered SAR complex image rather than raw data, the proposed method for complex image data can achieve a similar reconstructed image quality as the regularization-based SAR imaging approach using the full raw data. The most important contribution of this paper is that the proposed CAMP-based methods make CFAR detection based on the regularization reconstruction SAR image possible using their nonsparse scene estimations, which has a similar background statistical distribution as the MF recovered images. The experimental results validated the effectiveness of the proposed methods and the feasibility of the recovered nonsparse images being used for CFAR detection.

Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction

Tube current modulation (TCM) is routinely adopted on diagnostic CT scanners for dose reduction. Conventional TCM strategies are generally designed for filtered-backprojection (FBP) reconstruction to satisfy simple image quality requirements based on noise. This work investigates TCM designs for model-based iterative reconstruction (MBIR) to achieve optimal imaging performance as determined by a task-based image quality metric. Additionally, regularization is an important aspect of MBIR that is jointly optimized with TCM, and includes both the regularization strength that controls overall smoothness as well as directional weights that permits control of the isotropy/anisotropy of the local noise and resolution properties. Initial investigations focus on a known imaging task at a single location in the image volume. The framework adopts Fourier and analytical approximations for fast estimation of the local noise power spectrum (NPS) and modulation transfer function (MTF)—each carrying dependencies on TCM and regularization. For the single location optimization, the local detectability index (d′) of the specific task was directly adopted as the objective function. A covariance matrix adaptation evolution strategy (CMA-ES) algorithm was employed to identify the optimal combination of imaging parameters. Evaluations of both conventional and task-driven approaches were performed in an abdomen phantom for a mid-frequency discrimination task in the kidney. Among the conventional strategies, the TCM pattern optimal for FBP using a minimum variance criterion yielded a worse task-based performance compared to an unmodulated strategy when applied to MBIR. Moreover, task-driven TCM designs for MBIR were found to have the opposite behavior from conventional designs for FBP, with greater fluence assigned to the less attenuating views of the abdomen and less fluence to the more attenuating lateral views. Such TCM patterns exaggerate the intrinsic anisotropy of the MTF and NPS as a result of the data weighting in MBIR. Directional penalty design was found to reinforce the same trend. The task-driven approaches outperform conventional approaches, with the maximum improvement in d′ of 13% given by the joint optimization of TCM and regularization. This work demonstrates that the TCM optimal for MBIR is distinct from conventional strategies proposed for FBP reconstruction and strategies optimal for FBP are suboptimal and may even reduce performance when applied to MBIR. The task-driven imaging framework offers a promising approach for optimizing acquisition and reconstruction for MBIR that can improve imaging performance and/or dose utilization beyond conventional imaging strategies.

Imaging performance improvement of coherent extreme-ultraviolet scatterometry microscope with high-harmonic-generation extreme-ultraviolet source

In extreme-ultraviolet (EUV) lithography, the development of a review apparatus for the EUV mask pattern at an exposure wavelength of 13.5 nm is required. The EUV mask is composed of an absorber pattern and a Mo/Si multilayer on a glass substrate. This mask pattern has a three-dimensional (3D) structure. The 3D structure would modulate the EUV reflection phase, which would cause focus and pattern shifts. Thus, the review of the EUV phase image is also important. We have developed a coherent EUV scatterometry microscope (CSM), which is a simple microscope without objective optics. The EUV phase and intensity images were reconstructed with diffraction images by ptychography. For a standalone mask review, the high-harmonic-generation (HHG) EUV source was employed. In this study, we updated the sample stage, pump-laser reduction system, and gas-pressure control system to reconstruct the image. As a result, an 88 nm line-and-space pattern and a cross-line pattern were reconstructed. In addition, a particle defect of 2 µm diameter was well reconstructed. This demonstrated the high capability of the standalone CSM, which can hence be used in factories, such as mask shops and semiconductor fabrication plants.

Task-Driven Orbit Design and Implementation on a Robotic C-Arm System for Cone-Beam CT.

This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d'. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the fz-axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the (fy , fz ) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. For the fz -axis task, the circle + arc orbit was shown to increase d' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d' was increased by a factor of 1.83. This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

Microwave Imaging Using Normal Electric-Field Components Inside Metallic Resonant Chambers

A novel 3-D microwave imaging approach performed within a resonant air-filled metallic chamber is introduced and investigated. The new method utilizes the measurements of normal electric-field components at discrete points along the metallic chamber’s wall—near the chamber-wall boundary, the normal-field components are dominant, while the tangential components vanish. The inversion algorithm fully incorporates the resonant features of the low-loss chamber. A numerical study is used to quantify the imaging performance of using this technique compared with the traditional unbounded domain imaging. An experimental system is presented where the electric field is collected using 24 antennas distributed in three circumferential layers around an object of interest located inside the circular-cylindrical metallic chamber. For collecting the normal component of the field, two types of linearly polarized antennas are investigated: $\lambda /4$ monopole antennas and specially designed reconfigurable antennas (RAs), both projecting perpendicularly out from the chamber walls into the enclosure. The measured data are calibrated and then inverted using a multiplicatively regularized finite-element contrast source inversion algorithm. Using 3-D reconstructions of simple dielectric targets, it is shown that utilizing the RAs improves imaging performance due to a reduction in the modeling error introduced in the inversion algorithm.

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.

基于亚像素扫描的超分辨技术在高分辨X射线显微镜中的应用

Developing super-resolution scanning and reconstruction method on the existing hardware can improve imaging performance and saving the cost to upgrade hardware. In this paper, a super-resolution scanning mode based on sub-pixel scanning is designed and a series of low-resolution images of the sample is acquired through modulating the position of the sample. Then, the point spread function derived by processing the edge spread function is employed to the image restoration of the low-resolution image series. Finally, super-resolution reconstruction algorithm based on POCS is used to reconstruct super-resolution images. The experiments conducted on the high-resolution X-ray microscope equipped with a 10 times optical lens coupling detector show that the contrast-to-noise ratio increases about 20%, the spatial resolution has been improved about 0.2 μ m (about 15%), the detail resolution can exceed the limits of pixel size of the detector and more details are seen than low-resolution images. The experiment's results illustrate that the super-resolution technique has great potential in improving the spatial resolution of the high-resolution X-ray microscope. © 2017, Science Press. All right reserved.

Improvement of imaging performance for X-ray image tube

Improvement of imaging performance for X-ray image tube

Daubechies 정상 웨이블릿을 이용한 무인항공기 촬영 영상 성능 개선

본 논문은 Daubechies 정상 웨이블릿 변환을 이용하여 무인항공기 항공촬영 영상의 성능을 향상하기 위한 기법에 대해 연구하였다. 무인항공기에서 획득된 영상이 가장 일반적이고 보편적으로 적용되는 가우시안 잡음에 의하여 손상되었을 경우, 영상의 성능을 개선하기 위한 실험을 수행하였다. 정상 웨이블릿 변환은 DWT (discrete wavlet transform)에서 다운샘플링에 의해 발생하는 문제점을 해결하기 위한 변환방법으로써 잡음제거에 DWT보다 효과적이라고 알려져 있다. 또한 Haar 웨이블릿은 불연속 함수인 이유로 매끄러운 신호나 영상처리에 효과적이지 못하다. 이에 본 연구에서는 daubechies 정상 웨이블릿을 이용하여 잡음을 제거하였으며 기존 haar 정상 웨이블릿을 적용하였을 때 보다 더 성능이 개선됨을 확인하였다. In this paper, we study the technique to improve the performance of the aerial images taken by UAV using daubechies stationary wavelet transform. When aerial images taken by UAV were damaged by gaussian noise very commonly applied, the experiment for image performance improvement was performed. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. Also haar wavelet is discontinuous function so not efficient for smooth signal and image processing. Therefore, this study is confirmed that the noise can be removed by daubechies stationary wavelet and the performance is improved by haar stationary wavelet.

Saturated pattern-illuminated Fourier ptychography microscopy

We report a series of simulation studies which extends pattern-illuminated Fourier ptychography microscopy by integrating with the nonlinearity arising from saturation of the fluorophore excited state for super-resolution fluorescence imaging. This extended technique, termed Saturated pattern-illuminated Fourier ptychography (SpiFP) microscopy, could achieve a resolution four times that of wide field when the illuminating light intensity approaches the saturation threshold in simulations. Increasing light intensity leads to further resolution enhancement. In order to demonstrate the performance of SpiFP, we make a comparison between SpiFP and saturated structure illumination microscopy in simulations, and prove that the SpiFP exhibits superior robustness to noise, aberration correcting ability, and pattern’s flexibility. Introducing the saturation of the fluorescent emission brings in notable improvements in imaging performance, implying its potential in nanoscale-sized biological observations by wide-field microscopy.

A Depth-of-Interaction encoding method for SPECT monolithic scintillation detectors

The Depth of Interaction (DoI) discrimination of gamma-photons within scintillation crystals allows to improve imaging performance in PET scanners as well as in SPECT devices equipped with non-parallel collimators (e. g. pinhole ones). In previous works, the authors experimentally proved the efficiency of a DoI-encoding technique in case of a 20 mm-thick monolithic crystal PET module. For the thinner crystals commonly used in SPECT, DoI determination still remains a challenging goal. To this aim, in this work the authors have experimentally evaluated the DoI-encoding method on a 6 mm-thick monolithic LaBr3:Ce crystal. The results prove the efficiency and reliability of the proposed method. It indeed allows to discriminate the gamma photons interacting at the the top and the bottom of the crystal.

Efficient compressed imaging method for a microsatellite optical camera.

Imaging integrated with compression is considered the holy grail of microsatellite photography because it improves the degree of integration of the camera system, removing the compression system, high capacity storage system, and high-speed image transmission system, which consume lots of resources of the satellite platform. In this paper, we propose an efficient compressed imaging method for remote sensing photography. We consider wavelet coefficients as pixels of a block-wise megapixel sensor (BMPS). We integrate the saliency information stage into the BMPS to perform compressed sampling (CS) in order to further improve imaging performance. In the compressed sensing process, we use transformed postwavelet coefficients to calculate saliency information of images in the postwavelet domain. According to different regions having different saliency information, the corresponding sensing resources are allocated to perform CS. CS can obtain the compressed discrete sparse samples of the original signal at a much lower sample rate than the Nyquist frequency. The discrete samples signal can be reconstructed by a nonlinear recovery algorithm in the ground. Experimental results show that the proposed compressed imaging method outperforms the traditional saliency-based methods in terms of multiple assessment approaches.

Investigation of radiation detection properties of CRY-018 and CRY-019 scintillators for medical imaging

During the last years the research for new scintillation crystals has been crucial for the improvement of imaging performance in nuclear medicine applications. Crytur company has recently released two new scintillators named CRY-018 and CRY-019 which are non hygroscopic, have short decay time and low refraction index. They represent the ideal candidates to substitute NaI:Tl and BGO crystals in future PET ad SPECT applications. The purpose of this work is to characterize this unknown crystals, look for possible applications in imaging for nuclear medicine. The results of this work were compared with the results obtained with a LaBr3:ce scintillation crystal. This particular crystal is used as a comparison benchmark because of its strong linear pulse height uniformity response and high energy resolution. Measurements have been performed with a high count rate which is typical for medical applications. Irradiation of the crystals have been performed in three different geometries and in a photon energy range suitable with SPECT and PET applications. The experimental results identify the CRY-018 as an Yttrium and Silicon mixture and the CRY-019 with as Lutetium and Silicon one. Moreover a light yield of about 45% of LaBr3 one, was obtained for both the CRY-018 and CRY-019. This is one of the higher light yield between most of the scintillation crystals usually used in nuclear medicine. Both crystals are characterized by a non-proportionality in the pulse height linearity response. Energy resolutions of 7.4% for CRY-018 and 8.4% for CRY-019 at 661 keV, have been measured. The intrinsic component of the energy resolution has been esteemed for all three scintillators. An intrinsic detection efficiency of about 45% at 122 keV for CRY-018 and 14% at 661 keV for CRY-019 has been measured. Compared with LaBr3:Ce efficiency, which is highly deteriorated by the coating required by the hygroscopicity, CRY-018 and CRY-019 are really interesting considering that these two samples are only 6 mm thick. Crytur's crystals seem to be suitable for nuclear medicine applications.

Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays

In this work, we propose using camera arrays coupled with coherent illumination as an effective method of improving spatial resolution in long distance images by a factor of ten and beyond. Recent advances in ptychography have demonstrated that one can image beyond the diffraction limit of the objective lens in a microscope. We demonstrate a similar imaging system to image beyond the diffraction limit in long range imaging. We emulate a camera array with a single camera attached to an $XY$ translation stage. We show that an appropriate phase retrieval based reconstruction algorithm can be used to effectively recover the lost high resolution details from the multiple low resolution acquired images. We analyze the effects of noise, required degree of image overlap, and the effect of increasing synthetic aperture size on the reconstructed image quality. We show that coherent camera arrays have the potential to greatly improve imaging performance. Our simulations show resolution gains of $10\times$ and more are achievable. Furthermore, experimental results from our proof-of-concept systems show resolution gains of $4\times - 7\times$ for real scenes. All experimental data and code is made publicly available on the project webpage. Finally, we introduce and analyze in simulation a new strategy to capture macroscopic Fourier Ptychography images in a single snapshot, albeit using a camera array.

Improvement of Imaging Performance with a New ASCOR Probe-Corrector in a 200 kV JEM-ARM200CF

Improvement of Imaging Performance with a New ASCOR Probe-Corrector in a 200 kV JEM-ARM200CF

TH‐CD‐207B‐09: Task‐Driven Fluence Field Modulation Design for Model‐Based Iterative Reconstruction in CT

Purpose:There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered‐backprojection (FBP) performance. This work investigates a prospective task‐driven optimization of FFM for model‐based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies.Methods:The task‐driven optimization framework utilizes an ultra‐low dose 3D scout as a patient‐specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized‐likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi‐min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA‐ES) algorithm. The task‐driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom.Results:The task‐driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task‐based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi‐min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom.Conclusion:Results from this investigation suggests the need to re‐evaluate conventional FFM strategies for MBIR. The task‐based optimization framework provides a promising approach that maximizes imaging performance under the same total dose constraint.