3D Hessian deconvolution of thick light-sheet <i>z</i>-stacks for high-contrast and high-SNR volumetric imaging

Zhe Zhang; Dongzhou Gou; Fan Feng; Ruyi Zheng; Ke Du; Hongrun Yang; Guangyi Zhang; Huitao Zhang; Louis Tao; Liangyi Chen; Heng Mao

doi:doi:10.1364/PRJ.388651

Photonics Research, 2020, 8 (6): 06001011, Published Online: Jun. 1, 2020

3D Hessian deconvolution of thick light-sheet z-stacks for high-contrast and high-SNR volumetric imaging Download： 814次

Zhe Zhang ^1†Dongzhou Gou ^2†Fan Feng ³Ruyi Zheng ²Ke Du ²Hongrun Yang ^2,4Guangyi Zhang ¹Huitao Zhang ⁵Louis Tao ³Liangyi Chen ^2,6,*Heng Mao ^1,5,7,*

Author Affiliations

¹ LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, China

² State Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing 100871, China

³ Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, School of Life Sciences, Peking University, Beijing 100871, China

⁴ School of Software and Microelectronics, Peking University, Beijing 100871, China

⁵ Beijing Advanced Innovation Center for Imaging Theory and Technology, Capital Normal University, Beijing 100871, China

⁶ e-mail: lychen@pku.edu.cn

⁷ e-mail: heng.mao@pku.edu.cn

Abstract

Due to its ability of optical sectioning and low phototoxicity,

z

-stacking light-sheet microscopy has been the tool of choice for in vivo imaging of the zebrafish brain. To image the zebrafish brain with a large field of view, the thickness of the Gaussian beam inevitably becomes several times greater than the system depth of field (DOF), where the fluorescence distributions outside the DOF will also be collected, blurring the image. In this paper, we propose a 3D deblurring method, aiming to redistribute the measured intensity of each pixel in a light-sheet image to in situ voxels by 3D deconvolution. By introducing a Hessian regularization term to maintain the continuity of the neuron distribution and using a modified stripe-removal algorithm, the reconstructed

z

-stack images exhibit high contrast and a high signal-to-noise ratio. These performance characteristics can facilitate subsequent processing, such as 3D neuron registration, segmentation, and recognition.

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Zhe Zhang, Dongzhou Gou, Fan Feng, Ruyi Zheng, Ke Du, Hongrun Yang, Guangyi Zhang, Huitao Zhang, Louis Tao, Liangyi Chen, Heng Mao. 3D Hessian deconvolution of thick light-sheet z-stacks for high-contrast and high-SNR volumetric imaging[J]. Photonics Research, 2020, 8(6): 06001011.

3D Hessian deconvolution of thick light-sheet z-stacks for high-contrast and high-SNR volumetric imaging Download： 814次

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