Evidence map›Paper›PMID 29938379›Full record

ArticleJournal of medical systems2018

An Augmented Reality Endoscope System for Ureter Position Detection.

Feng Yu, Enmin Song, Hong Liu, Yunlong Li, Jun Zhu, Chih-Cheng Hung

Abstract read
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In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. A High-Speed Hyperspectral Laparoscopic Imaging System.Proceedings of SPIE--the International Society for Optical Engineering · 2023
    Article
  3. Review
  4. 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.

Feng YuSchool of Computer and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Enmin SongSchool of Computer and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Hong LiuSchool of Computer and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. hl.cbib@gmail.com.ORCID http://orcid.org/0000-0002-3464-1418
Yunlong LiDepartment of Urology, Affiliated Kunsan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China.
Jun ZhuSchool of Computer and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Chih-Cheng HungCenter for Machine Vision and Security Research, Kennesaw State University, Kennesaw, GA, USA.

Funding

Clinical Medicine Science and Technology Projects in Jiangsu province BL2014056Medical Clinical Science and Technology Development Fund of Jiangsu University JLY20140051CNational Key R & D Program of China 2017YFC0112804National Natural Science Foundation of China 61370179the Fundamental Research Funds for the Central Universities HUST: 2016YXZD018the Fundamental Research Funds for the Central Universities HUST: 2017JYCX038
6 · The paper itself

Abstract

Iatrogenic injury of ureter in the clinical operation may cause the serious complication and kidney damage. To avoid such a medical accident, it is necessary to provide the ureter position information to the doctor. For the detection of ureter position, an ureter position detection and display system with the augmented ris proposed to detect the ureter that is covered by human tissue. There are two key issues which should be considered in this new system. One is how to detect the covered ureter that cannot be captured by the electronic endoscope and the other is how to display the ureter position that provides stable and high-quality images. Simultaneously, any delayed processing of the system should disturb the surgery. The aided hardware detection method and target detection algorithms are proposed in this system. To mark the ureter position, a surface-lighting plastic optical fiber (POF) with the encoded light-emitting diode (LED) light is used to indicate the ureter position. The monochrome channel filtering algorithm (MCFA) is proposed to locate the ureter region more precisely. The ureter position is extracted using the proposed automatic region growing algorithm (ARGA) that utilizes the statistical information of the monochrome channel for the selection of growing seed point. In addition, according to the pulse signal of encoded light, the recognition of bright and dark frames based on the aided hardware (BDAH) is proposed to expedite the processing speed. Experimental results demonstrate that the proposed endoscope system can identify 92.04% ureter region in average.

Indexed as

AlgorithmsUreterVirtual RealityEndoscopesEndoscopyHumansIatrogenic DiseaseAugmented realityAutomatic region growing algorithm (ARGA)Endoscope systemUreter injuryUreter position detection

Identifiers

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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.