Significance: Photoacoustic computed tomography (PACT) is a fast-growing imaging modality. In PACT, the image quality is degraded due to the unknown distribution of the speed of sound (SoS). Emerging initial pressure (IP) and SoS joint-reconstruction methods promise reduced artifacts in PACT. However, previous joint-reconstruction methods have some deficiencies. A more effective method has promising prospects in preclinical applications.Aim: We propose a multi-segmented feature coupling (MSFC) method for SoS-IP joint reconstruction in PACT.Approach: In the proposed method, the ultrasound detectors were divided into multiple sub-arrays with each sub-array and its opposite counterpart considered to be a pair. The delay and sum algorithm was then used to reconstruct two images based on a subarray pair and estimated a direction-specific SoS, based on image correlation and the orientation of the subarrays. Once the data generated by all pairs of subarrays were processed, an image that was optimized in terms of minimal feature splitting in all directions was generated. Further, based on the direction-specific SoS, a model-based method was used to directly reconstruct the SoS distribution.Results: Both phantom and animal experiments demonstrated feasibility and showed promising results compared with conventional methods, with less splitting and blurring and fewer distortions.Conclusions: The developed MSFC method shows promising results for both IP and SoS reconstruction. The MSFC method will help to optimize the image quality of PACT in clinical applications.
Utilizing reflective photons could circumvent the penetration limit of FMT, enabling reconstruction of fluorescence distribution near the surface regard less of the object size and extending its applications to surgical navigation and so on. Therefore, a time-domain reflective fluorescence molecular tomography (TD-rFMT) is proposed. The system excites and detects the emission light from the same angle within a field of view of 5 cm. Because the detected intensities of targets depend strongly on the depth, the reconstruction of targets in deep regions would be evidently affected. Therefore, a fluorescence yield reconstruction method with depth regularization and a weighted separation reconstruction strategy for lifetime are developed to enhance the performance for deep targets. Through simulations and phantom experiments, TD-rFMT is proved capable of reconstructing fluorescence distribution within a 2.5-cm depth with accurate reconstructed yield, lifetime, and target position(s).
As an emerging optical imaging modality, photoacoustic imaging provides optical absorption contrasts and ultrasonic high resolution. Artifacts appearing in photoacoustic computed tomography (PACT) always deteriorate image quality and resolution, and result in confusion of biological information. On the basis of different causing reasons, they are roughly classified as split artifacts and streak artifacts. Here we present an innovative Feature-Coupling (FC) method to weaken split artifacts with joint reconstruction of speed of sound and a new reconstruction algorithm, termed Contamination-Tracing Back-Projection (CTBP), is proposed for the mitigation of streak artifacts. The utility, effectiveness and robustness of our methods were demonstrated using numerical, phantom, and in vivo experiments.
Photoacoustic imaging is an emerging optical imaging modality which provides optical absorption contrasts and high resolution in the optical diffusive regime. In photoacoustic computed tomography (PACT), often times the detection of the photoacoustic signal only covers a partial solid angle less than 4π, due to experimental or economic constraints. Incomplete spatial coverage always jeopardizes image quality and resolution, and results in significant artifacts and missing of image features. This problem is referred to as “limited view” and has remained unsolved for decades. In this work, we present a new machine-learning-based method that is specifically designed to compensate for the missing information due to limited view. The robustness and effectiveness of our method were demonstrated using numerical, phantom, and in vivo experiments.
Photoacoustic imaging relies on diffused photons for optical contrast, and diffracted ultrasound for high resolution. As a tomographic imaging modality, often times an inverse problem of acoustic diffraction needs to be solved to reconstruct a photoacoustic image. The inverse problem is complicated by the fact that the acoustic properties, including the speed of sound distribution, in the image field of view are unknown. During reconstruction, subtle changes of the speed of sound in the acoustic ray path may accumulate and give rise to noticeable blurring in the image. Thus, in addition to the ultrasound detection bandwidth, inaccurate acoustic modeling, especially the unawareness of the speed of sound, defines the image resolution and influences image quantification. Here, we proposed a method termed feature coupling to jointly reconstruct the speed of sound distribution and a photoacoustic image with improved sharpness, at no additional hardware cost. In vivo experiments demonstrated the effectiveness and reliability of our method.
For fluorescence molecular tomography, higher spatial resolution can be achieved using minimally scattered early photons. Conventional reconstruction methods of early photon tomography (EPT) are based on the integral of temporal point spread function (TPSF), which may lead to poor image quality due to systematic noise and time mismatch between the TPSF data and forward model. The derivative of the rising portion of TPSF is proposed to be used in EPT to increase the performance of reconstruction because the derivative is less sensitive to noise and time mismatch than the integral. A method based on projected Tikhonov regularization with the reconstructed result of steepest descent algorithm as a priori information is developed. Using the derivative of TPSF, the method can achieve high spatial resolution in phantom experiments and is capable of separating targets with an edge–edge distance of 1.5 mm.
Fluorescence molecular imaging has been used to target tumors in mice with xenograft tumors. However, tumor imaging is largely distorted by the aggregation of fluorescent probes in the liver. A principal component analysis (PCA)-based strategy was applied on the in vivo dynamic fluorescence imaging results of three mice with xenograft tumors to facilitate tumor imaging, with the help of a tumor-specific fluorescent probe. Tumor-relevant features were extracted from the original images by PCA and represented by the principal component (PC) maps. The second principal component (PC2) map represented the tumor-related features, and the first principal component (PC1) map retained the original pharmacokinetic profiles, especially of the liver. The distribution patterns of the PC2 map of the tumor-bearing mice were in good agreement with the actual tumor location. The tumor-to-liver ratio and contrast-to-noise ratio were significantly higher on the PC2 map than on the original images, thus distinguishing the tumor from its nearby fluorescence noise of liver. The results suggest that the PC2 map could serve as a bioimaging marker to facilitate in vivo tumor localization, and dynamic fluorescence molecular imaging with PCA could be a valuable tool for future studies of in vivo tumor metabolism and progression.
Fluorescence probes have distinct yields and lifetimes when located in different environments, which makes the reconstruction of fluorescence molecular lifetime tomography (FMLT) challenging. To enhance the reconstruction performance of time-domain (TD) FMLT with heterogeneous targets, a self-guided L1 regularization projected steepest descent (SGL1PSD) algorithm is proposed. Different from other algorithms performed in time domain, SGL1PSD introduces a time-resolved strategy into fluorescence yield reconstruction. The algorithm consists of four steps. Step 1 reconstructs the initial yield map with full time gate strategy; steps 2–4 reconstruct the inverse lifetime map, the yield map, and the inverse lifetime map again with time-resolved strategy, respectively. The reconstruction result of each step is used as a priori for the reconstruction of the next step. Projected iterated Tikhonov regularization algorithm is adopted for the yield map reconstructions in steps 1 and 3 to provide a solution with iterative refinement and nonnegative constraint. The inverse lifetime map reconstructions in steps 2 and 4 are based on L1 regularization projected steepest descent algorithm, which employ the L1 regularization to reduce the ill-posedness of the high-dimensional nonlinear problem. Phantom experiments with heterogeneous targets at different edge-to-edge distances demonstrate that SGL1PSD can provide high resolution and quantification accuracy for TD FMLT.
Traditional spectral imaging systems mainly rely on spatial scanning or spectral scanning methods to acquire spatial and spectral features. The acquisition is time-consuming and cannot fully satisfy the need of monitoring dynamic phenomenon and observing different structures of the specimen simultaneously. To overcome these barriers, we develop a video-rate simultaneous multispectral imaging system built with a spectral multiplexed volume holographic grating (VHG) and few optical components. Four spectral multiplexed volume holograms optimized for four discrete spectral bands (centered at 488 nm, 530 nm, 590 nm and 620 nm) are recorded into an 8×12 mm photo-thermal refractive glass. The diffraction efficiencies of all the holograms within the multiplexed VHG are greater than 80%. With the high throughout multiplexed VHG, the system can work with both reflection and fluorescence modes and allow simultaneous acquisition of spectral and spatial information with a single exposure. Imaging experiments demonstrate that the multispectral images of the target illuminated with white light source can be obtained. Fluorescence images of multiple fluorescence objects (two glass beads filled with 20 uL 1.0 mg/mL quantum dots solutions that emit 530 ± 15 nm and 620 ± 15 nm fluorescence, respectively) buried 3 mm below the surface of a tissue mimicking phantom are acquired. The results demonstrate that the system can provide complementary information in fluorescence imaging. The design diagram of the proposed system is given to explain the advantage of compactness and flexibility in integrating with other imaging platforms.
Dynamic fluorescence molecular tomography (DFMT) is a valuable method to evaluate the metabolic process of contrast agents in different organs in vivo, and direct reconstruction methods can improve the temporal resolution of DFMT. However, challenges still remain due to the large time consumption of the direct reconstruction methods. An acceleration strategy using graphics processing units (GPU) is presented. The procedure of conjugate gradient optimization in the direct reconstruction method is programmed using the compute unified device architecture and then accelerated on GPU. Numerical simulations and in vivo experiments are performed to validate the feasibility of the strategy. The results demonstrate that, compared with the traditional method, the proposed strategy can reduce the time consumption by ∼90% without a degradation of quality.
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