- Published on
Dc-EEMF: Pushing depth-of-field limit of photoacoustic microscopy via decision-level constrained learning
- Authors
- Name
- Wangting Zhou
- Name
- Jiangshan He
- Name
- Tong Cai
- Name
- Lin Wang
- Name
- Zhen Yuan
- Name
- Xunbin Wei
- Name
- Xueli Chen
- Affiliation
- Center for Biomedical-photonics and Molecular Imaging, Xi’an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710126, China
- Affiliation
- School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi 710048, China
- Affiliation
- Faculty of Health Sciences, University of Macau, Macau, 999078, China
- Affiliation
- Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China; Biomedical Engineering Department, Peking University, Beijing 100081, China
Photoacoustic microscopy holds the potential to measure biomarkers’ structural and functional status without labels, which significantly aids in comprehending pathophysiological conditions in biomedical research. However, conventional optical-resolution photoacoustic microscopy (OR-PAM) is hindered by a limited depth-of-field (DoF) due to the narrow depth range focused on a Gaussian beam. Consequently, it fails to resolve sufficient details in the depth direction. Herein, we propose a decision-level constrained end-to-end multi-focus image fusion (Dc-EEMF) to push DoF limit of PAM. The DC-EEMF method is a lightweight siamese network that incorporates an artifact-resistant channel-wise spatial frequency as its feature fusion rule. The meticulously crafted U-Net-based perceptual loss function for decision-level focus properties in end-to-end fusion seamlessly integrates the complementary advantages of spatial domain and transform domain methods within Dc-EEMF. This approach can be trained end-to-end without necessitating post-processing procedures. Experimental results and numerical analyses collectively demonstrate our method’s robust performance, achieving an impressive fusion result for PAM images without a substantial sacrifice in lateral resolution. The utilization of Dc-EEMF-powered PAM has the potential to serve as a practical tool in preclinical and clinical studies requiring extended DoF for various applications.