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Computational multifocal microscopy

Authors :
He, Kuan
Wang, Zihao
Huang, Xiang
Wang, Xiaolei
Yoo, Seunghwan
Ruiz, Pablo
Gdor, Itay
Selewa, Alan
Ferrier, Nicola J.
Scherer, Norbert
Hereld, Mark
Katsaggelos, Aggelos K.
Cossairt, Oliver
Publication Year :
2018

Abstract

Despite recent advances, high performance single-shot 3D microscopy remains an elusive task. By introducing designed diffractive optical elements (DOEs), one is capable of converting a microscope into a 3D "kaleidoscope", in which case the snapshot image consists of an array of tiles and each tile focuses on different depths. However, the acquired multifocal microscopic (MFM) image suffers from multiple sources of degradation, which prevents MFM from further applications. We propose a unifying computational framework which simplifies the imaging system and achieves 3D reconstruction via computation. Our optical configuration omits chromatic correction grating and redesigns the multifocal grating to enlarge the tracking area. Our proposed setup features only one single grating in addition to a regular microscope. The aberration correction, along with Poisson and background denoising, are incorporated in our deconvolution-based fully-automated algorithm, which requires no empirical parameter-tuning. In experiments, we achieve the spatial resolutions of $0.35$um (lateral) and $0.5$um (axial), which are comparable to the resolution that can be achieved with confocal deconvolution microscopy. We demonstrate a 3D video of moving bacteria recorded at $25$ frames per second using our proposed computational multifocal microscopy technique.<br />Comment: first appearance on Arxiv, submitted to OSA BOE

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1809.01239
Document Type :
Working Paper