DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy
Authors: Joseph L. Greene, Suet YIng Chan, Qilin Deng, Jeffrey Alido, Alexandra Lion, Guorong Hu, Ruipeng Guo, Tongyu Li, +3 more
Organizations: Boston University, Department of Electrical and Computer Engineering, Boston, MA, 02215 · Current Address: Georgia Tech Research Institute, Electro-Optical Systems Lab, Atlanta, GA, 30332 · Boston University, Department of Biology, Boston, MA, 02215 · Harvard Medical School, Brigham and Women’s Hospital, Department of Orthopedic Surgery, Boston, MA, 02215 · Boston University, Neurophotonics Center, Boston, MA, 02215 · Boston University, Department of Biomedical Engineering, Boston, MA, 02215
Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to degradation in scattering tissue. We introduce DeepFilters, a scattering-aware deep optics framework that jointly optimizes a parameterized pupil filter and a digital-filter-based reconstruction network through a calibrated differentiable forward model to achieve broad generalization without retraining. Incorporating empirical scattering kernels, physics-guided regularization, and a hybrid genetic-gradient initialization strategy, DeepFilters extends the PSF from 16 micron to >400 micron in clear media and enables signal recovery beyond 120 micron deep in biological tissues, validated across fixed brain slices and sea urchin embryos.