Photoacoustic computed tomography (PACT) is a rapidly developing biomedical imaging modality and has attracted substantial attention in recent years. Image reconstruction from photoacoustic projections plays a critical role in image formation in PACT. Here we review six major classes of image reconstruction approaches developed in the past three decades, including delay and sum, filtered back projection, series expansion, time reversal, iterative reconstruction, and deep-learning-based reconstruction. The principal ideas and implementations of the algorithms are summarized, and their reconstruction performances under different imaging scenarios are compared. Major challenges, future directions, and perspectives for the development of image reconstruction algorithms in PACT are also discussed. This review provides a self-contained reference guide for beginners and specialists in the photoacoustic community, to facilitate the development and application of novel photoacoustic image reconstruction algorithms.
In photoacoustic tomography (PAT), image reconstruction has a fundamental impact on image quality and imaging speed. Among various reconstruction algorithms, the analytical filtered back-projection (FBP) and the numerical time reversal (TR) algorithms are two commonly used image reconstruction techniques in PAT. However, so far, no comprehensive studies are reported on the comparisons of FBP and TR algorithms. In this work, we compare these two algorithms from the perspectives of computational efficiency, robustness to non-ideal detection surfaces, and applicability to heterogeneous media. The results show that: 1) In terms of computational efficiency, FBP is typically faster than TR due to its flexibility in the selection of the reconstruction region. 2) For non-ideal detection surfaces-based reconstruction, FBP can provide more accurate amplitude information for the limited-view reconstruction and can produce fewer image artifacts for the sparse-view reconstruction. 3) For acoustically heterogeneous media, the TR algorithm can incorporate acoustic properties and thus can yield high-quality images, while FBP fails in this case. This study can help researchers gain a deeper understanding of the FBP and TR algorithms and is expected to provide a guide for the reasonable selection of PAT image reconstruction algorithms.
Photoacoustic tomography (PAT) is a fast-evolving biomedical imaging modality in recent years, which has unique applications in a range of biomedical fields. In PAT, image reconstruction is a critical step to produce high-quality optical absorption images from photoacoustic projections. To date, algorithms based on back projection are the most widely used image reconstruction techniques due to their simplicity and computational efficiency. However, images reconstructed by back projection contain negative intensities, which have no physical meanings and are essentially undesired artifacts. Here we study the formation mechanism, fundamental causes of the negativity artifacts in backprojection based PAT. Results show that limited detector bandwidth and limited view angle are two fundamental causes of the negativity artifacts. When the bandwidth of the detector is limited, back-projection signals will be distorted due to the loss of frequency contents and negativity artifacts thus occur. When the view angle of the detector is limited, photoacoustic signals propagating in three-dimensional space cannot be captured completely, resulting in negativity artifacts. This work provides a comprehensive understanding of the characteristics of negativity artifacts, which may promote the development of artifact-free image reconstruction algorithms.
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