Abstract: Photoacoustic-ultrasound dual-modal imaging represents an emerging hybrid imaging technique that combines the functional advantages of photoacoustic imaging with the high-resolution structural characterization capabilities of ultrasound imaging. This article comprehensively summarizes the research status and progress from both system-level and algorithmic perspectives. In hardware development, breakthroughs in novel ultrasound transducers and multimodal probe architecture designs have significantly enhanced tissue penetration depth and signal acquisition efficiency while reducing system complexity. In terms of imaging algorithms, the synergistic innovation of physics-model-driven and data-driven approaches has achieved precise quantitative reconstruction of optical absorption parameters and sound velocity. In particular, deep learning frameworks employing multimodal feature fusion and adaptive optimization strategies have effectively addressed the limitations of conventional methods in noise suppression and computational efficiency. This article not only provides a reference for theoretical research and clinical applications of multi-modal imaging technology but also explores its broad prospects in the development of intelligent diagnostic/therapeutic devices and precision medicine practices.