Add to BibSonomyAbstract
A performance comparison between three learning-based approaches for quantitative phase imaging in digital holographic microscopy is reported. We have compared the models' resulting noise level, phase discontinuities, and fitting and prediction times.
© 2022 The Author(s)
PDF Article | Presentation VideoMore Like This
Learning-based autofocusing regression model for Digital Lensless Holographic Microscopy
Manuel Montoya, Maria J. Lopera, and Carlos Trujillo
Tu4A.3 Digital Holography and Three-Dimensional Imaging (DH) 2022
Comparison of Simultaneously Captured Transport of Intensity and Digital Holographic Microscopy Retrieved Phases
Shane Carney, Ting Chean Khoo, Shahab Bahreini Jangjoo, Anna Sharikova, Supriya D. Mahajan, Alexander Khmaladze, and Jonathan Petruccelli
Tu4A.5 Digital Holography and Three-Dimensional Imaging (DH) 2022
Fast-iterative blind reconstruction algorithms for accurate quantitative phase images in phase-shifting digital holographic microscopy
Raul Castaneda, Carlos Buitrago, Jorge Garcia-Sucerquia, Aaron Robinson, and Ana Doblas
HTh5D.3 Digital Holography and Three-Dimensional Imaging (DH) 2020