Evidence map›Paper›PMID 27580914›Full record

ArticleMolecular imaging and biology2017

Reconstruction Method for In Vivo Bioluminescence Tomography Based on the Split Bregman Iterative and Surrogate Functions.

Shuang Zhang, Kun Wang, Hongbo Liu, Chengcai Leng, Yuan Gao, Jie Tian

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular imaging and biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Recent methodology advances in fluorescence molecular tomography.Visual computing for industry, biomedicine, and art · 2018
    Review
  4. Article
  5. A new Monte Carlo code for light transport in biological tissue.Medical & biological engineering & computing · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Shuang ZhangSino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819, China.
Kun WangKey Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China. kun.wang@ia.ac.cn.
Hongbo LiuKey Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China.
Chengcai LengKey Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China.
Yuan GaoKey Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China.
Jie TianKey Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People's Republic of China. tian@ieee.org.
Chinese Academy of Sciences · CNShandong Institute of Automation · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeBioluminescence tomography (BLT) can provide in vivo three-dimensional (3D) images for quantitative analysis of biological processes in preclinical small animal studies, which is superior than the conventional planar bioluminescence imaging. However, to reconstruct light sources under the skin in 3D with desirable accuracy and efficiency, BLT has to face the ill-posed and ill-conditioned inverse problem. In this paper, we developed a new method for BLT reconstruction, which utilized the mathematical strategies of the split Bregman iterative and surrogate functions (SBISF) method. PROCEDURES: The proposed method considered the sparsity characteristic of the reconstructed sources. Thus, the sparsity itself was regarded as a kind of a priori information, and the sparse regularization is incorporated, which can accurately locate the position of the sources. Numerical simulation experiments of multisource cases with comparative analyses were performed to evaluate the performance of the proposed method. Then, a bead-implanted mouse and a breast cancer xenograft mouse model were employed to validate the feasibility of this method in in vivo experiments.

resultsThe results of both simulation and in vivo experiments indicated that comparing with the L1-norm iteration shrinkage method and non-monotone spectral projected gradient pursuit method, the proposed SBISF method provided the smallest position error with the least amount of time consumption.

conclusionsThe SBISF method is able to achieve high accuracy and high efficiency in BLT reconstruction and hold great potential for making BLT more practical in small animal studies.

Indexed as

AlgorithmsAnimalsImaging, Three-DimensionalLuminescent MeasurementsMice, Inbred BALB CMice, NudeNumerical Analysis, Computer-AssistedTomography, OpticalXenograft Model Antitumor AssaysBioluminescence tomography reconstructionOptical molecular imagingSplit Bregman methodSurrogate Functions

Identifiers

PMID27580914
OpenAlexW2515925892

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.