Negativity artifacts in back-projection based photoacoustic tomography. (27th November 2020)

• Record Type: Journal Article
• Authors: Shen, Kang; Liu, Songde; Feng, Ting; Yuan, Jie; Zhu, Benpeng; Tian, Chao
• Is Part Of: Journal of physics. Volume 54:Number 7(2021)
• Publication Date: 2020-11-27
• Subjects: photoacoustic tomography -- image reconstruction -- back projection -- point spread function -- negativity artifacts; Physics -- Periodicals; 530
• DOI: 10.1088/1361-6463/abc37d
• Languages: English
• ISSNs: 0022-3727

Abstract

Abstract: Photoacoustic tomography (PAT) has become a fast-evolving biomedical imaging modality in recent years. In PAT, image reconstruction is a critical step to produce high-quality photoacoustic images from raw photoacoustic signals. 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 values, especially at the edge of photoacoustic sources, which have no physical meaning and are essentially undesired artifacts. In this work, we study the formation mechanism, fundamental causes and removal strategies of the negativity artifacts in back-projection-based PAT. Our results show that limited detector bandwidth and limited view angle are two fundamental causes of negativity artifacts. When the bandwidth of a detector is limited, back-projection signals will be distorted as a result of the loss of frequency contents and negativity artifacts thus appear. When the view angle of the detector is limited, photoacoustic signals propagating in three-dimensional space will be partially lost, resulting in negativity artifacts. Post-processing strategies, such as envelope detection and forced zeroing can be used to remove the negativity artifacts but may cause problems. Since negativity artifacts are a common image quality degradation factor in PAT, understanding their characteristics may expedite the development of novel artifact-removal techniques and artifact-free image reconstruction algorithms, which are of importance to correct image interpretation and quantitative imaging.