E2E-BPF microscope: extended depth-of-field microscopy using learning-based implementation of binary phase filter and image deconvolution

The research team, led by Professor Chulmin Joo from the Department of Mechanical Engineering has developed a depth-of-field (DoF) extension computational imaging platform, the E2E-BPF microscope. Conventional microscopes face challenges in acquiring high-resolution, large DoF images due to the intrinsic trade-off between DoF and resolution. The research team resolved this intrinsic problem by designing a binary phase filter (BPF) using deep learning and jointly optimizing the image reconstruction network. This novel computational imaging platform allows for approximately 16-fold enhancement in DoF, when compared to conventional microscope with the same numerical aperture. The research outcome was published on November 13, 2023, in the journal 'Light: Science & Applications' (IF : 19.4). Recognizing the significance of the research findings, it has been extensively covered and highlighted by various domestic and international media, including the 'National Research Foundation of Korea', 'Electronic Newspaper', 'Wiley Analytical Science' and 'EurekAlert'.

The link: https://doi.org/10.1038/s41377-023-01300-5