SlingBAG: point cloud-based iterative algorithm for large-scale 3D photoacoustic imaging.

ABSTRACT: Large-scale 3D photoacoustic imaging has become increasingly important for both clinical and pre-clinical applications. Limited by cost and system complexity, only systems with sparsely-distributed sensors can be widely implemented, which necessitates advanced reconstruction algorithms to reduce artifacts. However, the high computing memory and time consumption of traditional iterative reconstruction (IR) algorithms is practically unacceptable for large-scale 3D photoacoustic imaging. Here, we propose a point cloud-based IR algorithm that reduces memory consumption by several orders, wherein the 3D photoacoustic scene is modeled as a series of Gaussian-distributed spherical sources stored in form of point cloud. During the IR process, not only are properties of each Gaussian source, includ

SUBMITTER: Li S 

PROVIDER: S-EPMC12775460 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature