Evidence map›Paper›PMID 32341846›Full record

ArticleBiomedical optics express2020

Phase unwrapping based on a residual en-decoder network for phase images in Fourier domain Doppler optical coherence tomography.

Chuanchao Wu, Zhengyu Qiao, Nan Zhang, Xiaochen Li, Jingfan Fan, Hong Song, Danni Ai, Jian Yang, Yong Huang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. On the use of deep learning for phase recovery.Light, science & applications · 2024
    Review
  2. Journal of biomedical optics · 2023
    Article
  3. 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

9 authors.

Chuanchao WuSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Zhengyu QiaoSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Nan ZhangSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Xiaochen LiSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Jingfan FanSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Hong SongSchool of Computer Science and Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Danni AiSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Jian YangSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.
Yong HuangSchool of Optics and Photonics, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To solve the phase unwrapping problem for phase images in Fourier domain Doppler optical coherence tomography (DOCT), we propose a deep learning-based residual en-decoder network (REDN) method. In our approach, we reformulate the definition for obtaining the true phase as obtaining an integer multiple of 2

Identifiers

PMID32341846
PMCPMC7173896

What OpenQuestion holds

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Registered trials

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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.