Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.
Authors
Affiliations (7)
Affiliations (7)
- The Laboratory of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai 201306, China.
- School of Electronic Engineering and Intelligent Manufacturing, Anqing Normal University, Anqing 246133, Anhui, China.
- The Laboratory of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai 201306, China. [email protected].
- School of Engineering, Great Bay University, Dongguan 523000, Guangdong, China.
- Department of Cell Biology & Medical Genetics, School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen 518060, Guangdong, China.
- Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong 999077, China.
- Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong 999077, China. [email protected].
Abstract
Photoacoustic imaging (PAI), a modality that combines the high contrast of optical imaging with the deep penetration of ultrasound, is rapidly transitioning from preclinical research to clinical practice. However, its widespread clinical adoption faces challenges such as the inherent trade-off between penetration depth and spatial resolution, along with the demand for faster imaging speeds. This review comprehensively examines the fundamental principles of PAI, focusing on three primary implementations: photoacoustic computed tomography, photoacoustic microscopy, and photoacoustic endoscopy. It critically analyzes their respective advantages and limitations to provide insights into practical applications. The discussion then extends to recent advancements in image reconstruction and artifact suppression, where both conventional and deep learning (DL)-based approaches have been highlighted for their role in enhancing image quality and streamlining workflows. Furthermore, this work explores progress in quantitative PAI, particularly its ability to precisely measure hemoglobin concentration, oxygen saturation, and other physiological biomarkers. Finally, this review outlines emerging trends and future directions, underscoring the transformative potential of DL in shaping the clinical evolution of PAI.