A Camera-Like Dual-Defocus Curvature Wavefront Sensor With GPU Acceleration for Real-Time Quantitative Phase Imaging

Due to the high-contrast imaging capability for label-free cells, diverse quantitative phase imaging (QPI) systems have been developed. However, most existing solutions exhibit limitations, including incompatibility with commercial microscopes, bulky/complex architectures, and restricted frame rates caused by computationally intensive phase reconstruction processes, thereby hindering their applicability in dynamic QPI scenarios. To overcome these challenges, we developed a camera-like curvature wavefront sensor (CWS) that integrates simultaneous dual-view transport-of-intensity phase imaging with parallel computing. The cost-effective system comprises a prism and dual-CMOS sensor within a compact size of 55.7 × 58.0 × 49.4 mm³ compatible with commercial microscopes. Operating at 20 frames per second (fps) with 1024 × 1024-pixel resolution, it enables real-time image acquisition, phase retrieval, data storage, and result visualization. Experimental validation confirmed its robust performance in field-of-view (FoV) correction, phase recovery accuracy, and computational efficiency. Practical utility was demonstrated through QPI-based flow cytometry and live-cell dynamic imaging applications. This plug-and-play, imaging system compatible, and cost-effective CWS platform offers a versatile solution for practical QPI requirements.