Reconstructing Patched or Partial Holograms to allow for Whole Slide Imaging with a Self-Referencing Holographic Microscope
Philip Groult, Julia D. Sistermanns, Ellen Emken, Oliver Hayden, Wolfgang Utschick
TL;DR
This work tackles the challenge of marrying whole slide imaging (WSI) with quantitative phase imaging (QPI) by using a self-referencing three-wave digital holographic microscope (DHM). It introduces an adaptive reconstruction pipeline that handles cutouts and patched holograms, employing gradient extraction from the Fourier spectrum and phase integration via Iterative Least Squares (ILS) with Mirrored Derivative Integration (MDI), plus an adapted integration for patch-based data. The results show that MDI improves accuracy for cutouts and that whole-slide reconstructions reduce patch-line artifacts, with an additional adapted integration further boosting robustness, though at higher computational cost. The study demonstrates practical feasibility of QPI-enabled WSI on cervical smears, offering a path toward high-throughput, information-rich cytology imaging and potential CAD applications.
Abstract
The last decade has seen significant advances in computer-aided diagnostics for cytological screening, mainly through the improvement and integration of scanning techniques such as whole slide imaging (WSI) and the combination with deep learning. Simultaneously, new imaging techniques such as quantitative phase imaging (QPI) are being developed to capture richer cell information with less sample preparation. So far, the two worlds of WSI and QPI have not been combined. In this work, we present a reconstruction algorithm which makes whole slide imaging of cervical smears possible by using a self-referencing three-wave digital holographic microscope. Since a WSI is constructed by combining multiple patches, the algorithm is adaptive and can be used on partial holograms and patched holograms. We present the algorithm for a single shot hologram, the adaptations to make it flexible to various inputs and show that the algorithm performs well for the tested epithelial cells. This is a preprint of our paper, which has been accepted for publication in 2026 IEEE International Symposium on Biomedical Imaging (ISBI).
