Simulation and analysis of an imaging detection device for wound contamination caused by transuranic nuclides / 中国辐射卫生

Objective To address the radioactive contamination of wounds caused by transuranic nuclides, wound radiation imaging based on coded aperture imaging technology was investigated. Methods By simulating multiple source terms using Monte Carlo method, the differences in imaging performance between two image reconstruction algorithms under near-field conditions were compared. The effects of detector pixels and detection plane pixels on image resolution were investigated. Results The imaging system was simulated based on the designed dimensions. The simulated imaging field of view was 89.4 mm × 89.4 mm and the simulated angular resolution was 1.98°. Based on the comparison of the average width at half height of the reconstructed point sources under different conditions, it was found that increasing the number of pixels in the detector and detection plane optimized the angular resolution but significantly prolonged the Monte Carlo simulation time. Conclusion According to the simulation results, the parameters of the imaging system can be used to effectively image radioactive contamination. Our results provide methodological support for the measurement of wound contamination caused by transuranic nuclides, and lay the foundation for the development of wound contamination imaging detection systems in the future.

Coded aperture and Compton imaging for the development of 225 Ac-based radiopharmaceuticals.

BACKGROUND: Targeted alpha-particle therapy (TAT) has great promise as a cancer treatment. Arguably the most promising TAT radionuclide that has been proposed is 225 Ac. The development of 225 Ac-based radiopharmaceuticals has been hampered due to the lack of effective means to study the daughter redistribution of these agents in small animals at the preclinical stage. PURPOSE: The ability to directly image the daughters, namely 221 Fr and 213 Bi, via their gamma-ray emissions would be a boon for preclinical studies. That said, conventional medical imaging modalities, including single photon emission computed tomography (SPECT) based on nonmultiplexed collimation, cannot be employed due to sensitivity limitations. METHODS: As an alternative, we propose the use of both coded aperture and Compton imaging with the former modality suited to the 218-keV gamma-ray emission of 221 Fr and the latter suited to the 440-keV gamma-ray emission of 213 Bi. RESULTS: This work includes coded aperture images of 221 Fr and Compton images of 213 Bi in tumor-bearing mice injected with 225 Ac-based radiopharmaceuticals. CONCLUSIONS: These results are the first demonstration of visualizing and quantifying the 225 Ac daughters in small animals through the application of coded aperture and Compton imaging.

Monte Carlo and experimental evaluation of a Timepix4 compact gamma camera for coded aperture nuclear medicine imaging with depth resolution.

PURPOSE: We designed a prototype compact gamma camera (MediPROBE4) for nuclear medicine tasks, including radio-guided surgery and sentinel lymph node imaging with a 99mTc radiotracer. We performed Monte Carlo (MC) simulations for image performance assessment, and first spectroscopic imaging tests with a 300 µm thick silicon detector. METHODS: The hand-held camera (1 kg weight) is based on a Timepix4 readout circuit for photon-counting, energy-sensitive, hybrid pixel detectors (24.6 × 28.2 mm2 sensitive area, 55 µm pixel pitch), developed by the Medipix4 Collaboration. The camera design adopts a CdTe detector (1 or 2 mm thick) bump-bonded to a Timepix4 readout chip and a coded aperture collimator with 0.25 mm diameter round holes made of 3D printed 1-mm thick tungsten. Image reconstruction is performed via autocorrelation deconvolution. RESULTS: Geant4 MC simulations showed that, for a 99mTc source in air, at 50 mm source-collimator distance, the estimated collimator sensitivity (4 × 10-4) is 292 times larger than that of a single hole in the mask; the system sensitivity is 0.22 cps/kBq (2 mm CdTe); the lateral spatial resolution is 1.7 mm FWHM. The estimated axial longitudinal resolution is 8.2 mm FWHM at 40 mm distance. First experimental tests with a 300 µm thick Silicon pixel detector bump-bonded to a Timepix4 chip and a high-resolution coded aperture collimator showed time-over-threshold and time-of-arrival capabilities with 241Am and 133Ba gamma-ray sources. CONCLUSIONS: MC simulations and validation lab tests showed the expected performance of the MediPROBE4 compact gamma camera for gamma-ray 3D imaging.

An Innovative Concept of a 3D-Coded Aperture Imaging System Proposed for Early Breast Cancer Detection.

Coded Aperture (CA) imaging has recently been used in nuclear medicine, but still, there is no commercial SPECT imaging camera based on CA for cancer detection. The literature is rich in examples of using the CA for planar and thin 3D imaging. However, thick 3D reconstruction is still challenging for small lesion detection. This paper presents the results of mosaic modified uniformly redundant array (MURA) mask/antimask CA combined with a maximum-likelihood expectation-maximization (MLEM) algorithm. The MLEM is an iterative algorithm applied to a mosaic MURA CA mask/antimask for 3D anthropomorphic breast phantom reconstruction, slice by slice. The difference between the mask and the antimask suppresses the background noise to enhance the quality of reconstructed images. Furthermore, all reconstructed slices are stacked to form a 3D breast phantom image from single-projection data. The results of phantom reconstruction with 8 mm, 6 mm, 4 mm, and 3 mm lesions are presented. Moreover, the proposed SPECT imaging camera can reconstruct a 3D breast phantom from single-projection data of the patient's scanning. To assess the quality of lesions in the reconstructed images, the contrast-to-background ratio (CBR), the peak signal-to-noise ratio (PSNR) and mean square error (MSE) were measured.

Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks-Concepts and Review of Research.

Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object's image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object's image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR isinvestigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Neural network method for localization of radioactive sources within a partially coded field-of-view in coded-aperture imaging.

Coded-aperture imagers typically have a smaller field-of-view (FOV) than in un-collimated gamma imaging systems. However, sources out of the fully coded field-of-view (FCFOV) can cause pseudo hotspots on the wrong side of an image reconstructed using the cross-correlation method. In this work, we propose a neural network method to identify and localize the sources within the partially coded field-of-view (PCFOV). The model was trained using Monte Carlo simulation data and evaluated with both simulation and experimental data. The results showed that the proposed model can identify and localize sources with good classification accuracy, low positioning error, and strong robustness to the statistical noise.

Reduction in Irradiation Dose in Aperture Coded Enhanced Computed Tomography Imager Using Super-Resolution Techniques.

One of the main concerns regarding medical imaging is the danger tissue's ionizing due to the applied radiation. Many medical procedures are based on this ionizing radiation (such as X-rays and Gamma radiation). This radiation allows the physician to perform diagnosis inside the human body. Still, the main concern is stochastic effects to the DNA, particularly the cause of cancer. The radiation dose endangers not only the patient but also the medical staff, who might be close to the patient and be exposed to this dangerous radiation in a daily manner. This paper presents a novel concept of radiation reduced Computed Tomography (CT) scans. The proposed concept includes two main methods: minification to enhance the energy concertation per pixel and subpixel resolution enhancement, using shifted images, to preserve resolution. The proposed process uses several pinhole masks as the base of the imaging modality. The proposed concept was validated numerically and experimentally and has demonstrated the capability of reducing the radiation efficiency by factor 4, being highly significant to the world of radiology and CT scans. This dose reduction allows a safer imaging process for the patient and the medical staff. This method simplifies the system and improves the obtained image quality. The proposed method can contribute additively to standard existing dose reduction or super-resolution techniques to achieve even better performance.

Gamma Radiation Imaging System via Variable and Time-Multiplexed Pinhole Arrays.

Biomedical planar imaging using gamma radiation is a very important screening tool for medical diagnostics. Since lens imaging is not available in gamma imaging, the current methods use lead collimator or pinhole techniques to perform imaging. However, due to ineffective utilization of the gamma radiation emitted from the patient's body and the radioactive dose limit in patients, poor image signal to noise ratio (SNR) and long image capturing time are evident. Furthermore, the resolution is related to the pinhole diameter, thus there is a tradeoff between SNR and resolution. Our objectives are to reduce the radioactive dose given to the patient and to preserve or improve SNR, resolution and capturing time while incorporating three-dimensional capabilities in existing gamma imaging systems. The proposed imaging system is based on super-resolved time-multiplexing methods using both variable and moving pinhole arrays. Simulations were performed both in MATLAB and GEANT4, and gamma single photon emission computed tomography (SPECT) experiments were conducted to support theory and simulations. The proposed method is able to reduce the radioactive dose and image capturing time and to improve SNR and resolution. The results and method enhance the gamma imaging capabilities that exist in current systems, while providing three-dimensional data on the object.

Phaseless Terahertz Coded-Aperture Imaging for Sparse Target Based on Phase Retrieval Algorithm.

Phaseless terahertz coded-aperture imaging (PL-TCAI) is a novel radar computational imaging method that utilizes the coded aperture and the incoherent detector array to achieve forward-looking and high-resolution imaging without relying on relative motion. In this paper, we propose a more reasonable and compact architecture for the PL-TCAI system and derive the imaging model of PL-TCAI based on the random frequency-hopping signal. Since most phase retrieval algorithms for PL-TCAI utilize only the intensity of echo signals to accurately reconstruct the target, excessive measurement samples are usually required. In order to reduce the number of measurement samples required for imaging, this paper proposes a sparse Wirtinger flow algorithm with optimal stepsize (SWFOS) by using the sparse prior of the target. The specific procedures of the SWFOS algorithm include the support recovery, initialization by truncated spectral method, iteration via gradient descent scheme, hard threshold operation, and stepsize optimization of iteration. Numerical simulations are performed, and the results show that the SWFOS algorithm not only has good performance for the PR problem, but can also sharply reduce the number of measurement samples required for imaging in the PL-TCAI system.

Phaseless Terahertz Coded-Aperture Imaging Based on Incoherent Detection.

In this paper, we propose a phaseless terahertz coded-aperture imaging (PTCAI) method by using a single incoherent detector or an incoherent detection array. We at first analyze and model the system architecture, derive the matrix imaging equation, and then study the phase retrieval techniques to reconstruct the original target with high resolution. Numerical experiments are performed and the results show that the proposed method can significantly reduce the system complexity in the receiving process while maintaining high resolution imaging capability. Furthermore, the approach of using incoherent detection array instead of single detector is capable of decreasing the encoding and sampling times, and therefore helps to improve the imaging frame rate. In our future research, the method proposed in this paper will be experimentally tested and validated, and high-speed PTCAI at nearly real-time frame rates will be the main work.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Back Projection.

Terahertz coded-aperture imaging (TCAI) can overcome the difficulties of traditional radar in forward-looking and high-resolution imaging. Three-dimensional (3D) TCAI relies mainly on the reference-signal matrix (RSM), the large size and poor accuracy of which reduce the computational efficiency and imaging ability, respectively. According to the previous research on TCAI, traditional TCAI cannot reduce the heavy computational burden while the improved TCAI achieve reconstructing the target parts of different ranges in parallel. However, large-sized RSM still accounts for the computational complexity of traditional TCAI and the improved TCAI. Therefore, this paper proposes a more efficient imaging method named back projection (BP)-TCAI (BP-TCAI). Referring to the basic principle of BP, BP-TCAI can not only divide the scattering information in different ranges but also project the range profiles into different imaging subareas. In this way, the target parts in different subareas can be reconstructed simultaneously to synthesize the whole 3D target and thus decomposes the computational complexity thoroughly. During the pulse compression and projection processes, the signal-to-noise ratio (SNR) of BP-TCAI is also improved. This present the imaging method, model and procedures of traditional TCAI, the improved TCAI and the proposed BP-TCAI. Numerical experimental results prove BP-TCAI to be more effective and efficient than previous imaging methods of TCAI. Besides, BP-TCAI can also be seen as synthetic aperture radar (SAR) imaging with coding technology. Therefore, BP-TCAI opens a future gate combining traditional SAR and coded-aperture imaging.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Geometric Measures.

For synthetic aperture radars, it is difficult to achieve forward-looking and staring imaging with high resolution. Fortunately, terahertz coded-aperture imaging (TCAI), an advanced radar imaging technology, can solve this problem by producing various irradiation patterns with coded apertures. However, three-dimensional (3D) TCAI has two problems, including a heavy computational burden caused by a large-scale reference signal matrix, and poor resolving ability at low signal-to-noise ratios (SNRs). This paper proposes a 3D imaging method based on geometric measures (GMs), which can reduce the computational burden and achieve high-resolution imaging for low SNR targets. At extremely low SNRs, it is difficult to detect the range cells containing scattering information with an ordinary range profile. However, this difficulty can be overcome through GMs, which can enhance the useful signal and restrain the noise. By extracting useful data from the range profile, target information in different imaging cells can be simultaneously reconstructed. Thus, the computational complexity is distinctly reduced when the 3D image is obtained by combining reconstructed 2D imaging results. Based on the conventional TCAI (C-TCAI) model, we deduce and build a GM-based TCAI (GM-TCAI) model. Compared with C-TCAI, the experimental results demonstrate that GM-TCAI achieves a more impressive performance with regards to imaging ability and efficiency. Furthermore, GM-TCAI can be widely applied in close-range imaging fields, for instance, medical diagnosis, nondestructive detection, security screening, etc.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Matched Filtering and Convolutional Neural Network.

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. However, there are still two problems in three-dimensional (3D) TCAI. Firstly, the large-scale reference-signal matrix based on meshing the 3D imaging area creates a heavy computational burden, thus leading to unsatisfactory efficiency. Secondly, it is difficult to resolve the target under low signal-to-noise ratio (SNR). In this paper, we propose a 3D imaging method based on matched filtering (MF) and convolutional neural network (CNN), which can reduce the computational burden and achieve high-resolution imaging for low SNR targets. In terms of the frequency-hopping (FH) signal, the original echo is processed with MF. By extracting the processed echo in different spike pulses separately, targets in different imaging planes are reconstructed simultaneously to decompose the global computational complexity, and then are synthesized together to reconstruct the 3D target. Based on the conventional TCAI model, we deduce and build a new TCAI model based on MF. Furthermore, the convolutional neural network (CNN) is designed to teach the MF-TCAI how to reconstruct the low SNR target better. The experimental results demonstrate that the MF-TCAI achieves impressive performance on imaging ability and efficiency under low SNR. Moreover, the MF-TCAI has learned to better resolve the low-SNR 3D target with the help of CNN. In summary, the proposed 3D TCAI can achieve: (1) low-SNR high-resolution imaging by using MF; (2) efficient 3D imaging by downsizing the large-scale reference-signal matrix; and (3) intelligent imaging with CNN. Therefore, the TCAI based on MF and CNN has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Single Input Multiple Output Technology.

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. In this paper, we propose a three-dimensional (3D) TCAI architecture based on single input multiple output (SIMO) technology, which can reduce the coding and sampling times sharply. The coded aperture applied in the proposed TCAI architecture loads either purposive or random phase modulation factor. In the transmitting process, the purposive phase modulation factor drives the terahertz beam to scan the divided 3D imaging cells. In the receiving process, the random phase modulation factor is adopted to modulate the terahertz wave to be spatiotemporally independent for high resolution. Considering human-scale targets, images of each 3D imaging cell are reconstructed one by one to decompose the global computational complexity, and then are synthesized together to obtain the complete high-resolution image. As for each imaging cell, the multi-resolution imaging method helps to reduce the computational burden on a large-scale reference-signal matrix. The experimental results demonstrate that the proposed architecture can achieve high-resolution imaging with much less time for 3D targets and has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

Multiplexed coded illumination for Fourier Ptychography with an LED array microscope.

Fourier Ptychography is a new computational microscopy technique that achieves gigapixel images with both wide field of view and high resolution in both phase and amplitude. The hardware setup involves a simple replacement of the microscope's illumination unit with a programmable LED array, allowing one to flexibly pattern illumination angles without any moving parts. In previous work, a series of low-resolution images was taken by sequentially turning on each single LED in the array, and the data were then combined to recover a bandwidth much higher than the one allowed by the original imaging system. Here, we demonstrate a multiplexed illumination strategy in which multiple randomly selected LEDs are turned on for each image. Since each LED corresponds to a different area of Fourier space, the total number of images can be significantly reduced, without sacrificing image quality. We demonstrate this method experimentally in a modified commercial microscope. Compared to sequential scanning, our multiplexed strategy achieves similar results with approximately an order of magnitude reduction in both acquisition time and data capture requirements.