Evidence map›Paper›PMID 31425010›Full record

ArticleIEEE transactions on bio-medical engineering2020

Accelerated Stimulated Raman Projection Tomography by Sparse Reconstruction From Sparse-View Data.

Xueli Chen, Shouping Zhu, Huiyuan Wang, Cuiping Bao, Defu Yang, Chi Zhang, Peng Lin, Ji-Xin Cheng, Yonghua Zhan, Jimin Liang and 1 more

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Article in IEEE transactions on bio-medical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Xueli Chen
Shouping Zhu
Huiyuan Wang
Cuiping Bao
Defu Yang
Chi Zhang
Peng Lin
Ji-Xin Cheng
Yonghua Zhan
Jimin Liang
Jie Tian

Funding

High-throughput high-content single cell analysis by multichannel stimulatedRaman flow cytometryR01GM118471 · NIGMS · PURDUE UNIVERSITY · PI CHENG, JI-XIN · 2016 to 2019
$1.6M
NIGMS NIH HHS R01 GM118471
6 · The paper itself

Abstract

objectiveStimulated Raman projection tomography (SRPT), a recently developed label-free volumetric chemical imaging technology, has been reported to quantitatively reconstruct the distribution of chemicals in a three-dimensional (3D) complex system. The current image reconstruction scheme used in SRPT is based on a filtered back projection (FBP) algorithm that requires at least 180 angular-dependent projections to rebuild a reasonable SRPT image, resulting in a long total acquisition time. This is a big limitation for longitudinal studies on live systems.

methodsWe present a sparse-view data-based sparse reconstruction scheme, in which sparsely sampled projections at 180 degrees were used to reconstruct the volumetric information. In the scheme, the simultaneous algebra reconstruction technique (SART), combined with total variation regularization, was used for iterative reconstruction. To better describe the projection process, a pixel vertex driven model (PVDM) was developed to act as projectors, whose performance was compared with those of the distance driven model (DDM).

resultsWe evaluated our scheme with numerical simulations and validated it for SRPT by mapping lipid contents in adipose cells. Simulation results showed that the PVDM performed better than the DDM in the case of using sparse-view data. Our scheme could maintain the quality of the reconstructed images even when the projection number was reduced to 15. The cell-based experimental results demonstrated that the proposed scheme can improve the imaging speed of the current FBP-based SRPT scheme by a factor of 9-12 without sacrificing discernible imaging details.

conclusionOur proposed scheme significantly reduces the total acquisition time required for SRPT at a speed of one order of magnitude faster than the currently used scheme. This significant improvement in imaging speed would potentially promote the applicability of SRPT for imaging living organisms.

Indexed as

Image Processing, Computer-AssistedTomography, X-Ray ComputedAlgorithmsPhantoms, ImagingTomography

Identifiers

PMID31425010
PMCPMC7329365

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.