scholarly journals Accelerating iterative deconvolution and multiview fusion by orders of magnitude

2019 ◽  
Author(s):  
Min Guo ◽  
Yue Li ◽  
Yijun Su ◽  
Talley Lambert ◽  
Damian Dalle Nogare ◽  
...  
Keyword(s):  
Software Design ◽  
Single Cells ◽  
Light Sheet ◽  
Mouse Tissue ◽  
3D Image ◽  
Light Sheet Microscopy ◽  
Point Spread ◽  
Spread Function ◽  
Gpu Processing ◽  
Spatially Varying

AbstractWe describe theoretical and practical advances in algorithm and software design, resulting in ten to several thousand-fold faster deconvolution and multiview fusion than previous methods. First, we adapt methods from medical imaging, showing that an unmatched back projector accelerates Richardson-Lucy deconvolution by at least 10-fold, in most cases requiring only a single iteration. Second, we show that improvements in 3D image-based registration with GPU processing result in speedups of 10-100-fold over CPU processing. Third, we show that deep learning can provide further accelerations, particularly for deconvolution with a spatially varying point spread function. We illustrate the power of our methods from the subcellular to millimeter spatial scale, on diverse samples including single cells, nematode and zebrafish embryos, and cleared mouse tissue. Finally, we show that our methods facilitate the use of new microscopes that improve spatial resolution, including dual-view cleared tissue light-sheet microscopy and reflective lattice light-sheet microscopy.

scholarly journals Deconvolution of light sheet microscopy recordings

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Klaus Becker ◽  
Saiedeh Saghafi ◽  
Marko Pende ◽  
Inna Sabdyusheva-Litschauer ◽  
Christian M. Hahn ◽  
...  
Keyword(s):  
Point Spread Function ◽  
High Field ◽  
Light Sheet ◽  
Theoretical Point ◽  
Function Model ◽  
Point Spread Functions ◽  
Light Sheet Microscopy ◽  
Point Spread ◽  
Spread Function ◽  
Image Details

AbstractWe developed a deconvolution software for light sheet microscopy that uses a theoretical point spread function, which we derived from a model of image formation in a light sheet microscope. We show that this approach provides excellent blur reduction and enhancement of fine image details for image stacks recorded with low magnification objectives of relatively high NA and high field numbers as e.g. 2x NA 0.14 FN 22, or 4x NA 0.28 FN 22. For these objectives, which are widely used in light sheet microscopy, sufficiently resolved point spread functions that are suitable for deconvolution are difficult to measure and the results obtained by common deconvolution software developed for confocal microscopy are usually poor. We demonstrate that the deconvolutions computed using our point spread function model are equivalent to those obtained using a measured point spread function for a 10x objective with NA 0.3 and for a 20x objective with NA 0.45.

Blind deconvolution in autocorrelation inversion for multi-view light sheet microscopy

2021 ◽  
Author(s):  
Elena Corbetta ◽  
Alessia Candeo ◽  
Andrea Bassi ◽  
Daniele Ancora
Keyword(s):  
Point Spread Function ◽  
Blind Deconvolution ◽  
Light Sheet ◽  
Reconstruction Method ◽  
Light Sheet Microscopy ◽  
Point Spread ◽  
Spread Function ◽  
Unknown Point

AbstractCombining the information coming from multi-view acquisitions is a problem of great interest in light-sheet microscopy. Aligning the views and increasing the resolution of their fusion can be challenging, especially if the setup is not fully calibrated. Here, we tackle these issues by proposing a new reconstruction method based on autocorrelation inversion that avoids alignment procedures. On top of this, we add a blind deconvolution step to improve the resolution of the final reconstruction. Our method permits us to achieve inherently aligned, highly resolved reconstructions while, at the same time, estimating the unknown point-spread function of the system.

scholarly journals Tracking cells in epithelial acini by light sheet microscopy reveals proximity effects in breast cancer initiation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Ashna Alladin ◽  
Lucas Chaible ◽  
Lucia Garcia del Valle ◽  
Reither Sabine ◽  
Monika Loeschinger ◽  
...  
Keyword(s):  
Single Cells ◽  
Image Data ◽  
Integrated Approach ◽  
Light Sheet ◽  
Mammary Epithelial ◽  
Proximity Effects ◽  
Transformed Cells ◽  
Light Sheet Microscopy ◽  
Primary Mouse ◽  
Longitudinal Imaging

Cancer clone evolution takes place within tissue ecosystem habitats. But, how exactly tumors arise from a few malignant cells within an intact epithelium is a central, yet unanswered question. This is mainly due to the inaccessibility of this process to longitudinal imaging together with a lack of systems that model the progression of a fraction of transformed cells within a tissue. Here, we developed a new methodology based on primary mouse mammary epithelial acini, where oncogenes can be switched on in single cells within an otherwise normal epithelial cell layer. We combine this stochastic breast tumor induction model with inverted light-sheet imaging to study single-cell behavior for up to four days and analyze cell fates utilizing a newly developed image-data analysis workflow. The power of this integrated approach is illustrated by us finding that small local clusters of transformed cells form tumors while isolated transformed cells do not.

Satellite image restoration in the context of a spatially varying point spread function

2010 ◽  
Vol 27 (6) ◽  
pp. 1473 ◽  
Author(s):  
Nasreddine Hajlaoui ◽  
Caroline Chaux ◽  
Guillaume Perrin ◽  
Frédéric Falzon ◽  
Amel Benazza-Benyahia
Keyword(s):  
Image Restoration ◽  
Point Spread Function ◽  
Satellite Image ◽  
Point Spread ◽  
Spread Function ◽  
Spatially Varying

scholarly journals Reflective imaging improves resolution, speed, and collection efficiency in light sheet microscopy

2017 ◽  
Author(s):  
Yicong Wu ◽  
Abhishek Kumar ◽  
Corey Smith ◽  
Evan Ardiel ◽  
Panagiotis Chandris ◽  
...  
Keyword(s):  
High Resolution ◽  
High Speed ◽  
Collection Efficiency ◽  
Single Cells ◽  
Numerical Aperture ◽  
Light Sheet ◽  
Three Dimensions ◽  
Spatiotemporal Resolution ◽  
Light Sheet Microscopy ◽  
Simultaneous Acquisition

AbstractLight-sheet fluorescence microscopy (LSFM) enables high-speed, high-resolution, gentle imaging of live biological specimens over extended periods. Here we describe a technique that improves the spatiotemporal resolution and collection efficiency of LSFM without modifying the underlying microscope. By imaging samples on reflective coverslips, we enable simultaneous collection of multiple views, obtaining 4 complementary views in 250 ms, half the period it would otherwise take to collect only two views in symmetric dual-view selective plane illumination microscopy (diSPIM). We also report a modified deconvolution algorithm that removes the associated epifluorescence contamination and fuses all views for resolution recovery. Furthermore, we enhance spatial resolution (to < 300 nm in all three dimensions) by applying our method to a new asymmetric diSPIM, permitting simultaneous acquisition of two high-resolution views otherwise difficult to obtain due to steric constraints at high numerical aperture (NA). We demonstrate the broad applicability of our method in a variety of samples of moderate (< 50 μm) thickness, studying mitochondrial, membrane, Golgi, and microtubule dynamics in single cells and calcium activity in nematode embryos.

Sign in / Sign up

Export Citation Format

Share Document