Evidence map›Paper›PMID 28717560›Full record

ArticleBiomedical optics express2017

Ultra-high speed digital micro-mirror device based ptychographic iterative engine method.

Aihui Sun, Xiaoliang He, Yan Kong, Haoyang Cui, Xiaojun Song, Liang Xue, Shouyu Wang, Cheng Liu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

1 citing paper in PubMed, 23 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 1 country.

Aihui SunDepartment of Optoelectronic Information Science and Engineering, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China.
Xiaoliang HeShanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China.
Yan KongDepartment of Optoelectronic Information Science and Engineering, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China.
Haoyang CuiCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China.
Xiaojun SongCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China.
Liang XueCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China.
Shouyu WangDepartment of Optoelectronic Information Science and Engineering, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China.
Cheng LiuDepartment of Optoelectronic Information Science and Engineering, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China.
Jiangnan University · CNShanghai University of Electric Power · CNShanghai Institute of Optics and Fine Mechanics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To reduce the long data acquisition time of the common mechanical scanning based Ptychographic Iterative Engine (PIE) technique, the digital micro-mirror device (DMD) is used to form the fast scanning illumination on the sample. Since the transverse mechanical scanning in the common PIE is replaced by the on/off switching of the micro-mirrors, the data acquisition time can be reduced from more than 15 minutes to less than 20 seconds for recording 12 × 10 diffraction patterns to cover the same field of 147.08 mm

Indexed as

(100.5070) Phase retrieval(110.1650) Coherence imaging(110.1758) Computational imaging

Identifiers

PMID28717560
PMCPMC5508821
OpenAlexW2622534651

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.