Evidence map›Paper›PMID 30832271›Full record

ArticleSensors (Basel, Switzerland)2019

PDMS Microlenses for Focusing Light in Narrow Band Imaging Diagnostics.

Adriana C Costa, Sara Pimenta, João F Ribeiro, Manuel F Silva, Reinoud F Wolffenbuttel, Tao Dong, Zhaochu Yang, José H Correia

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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
0.2field-weighted citation impact, top 51% 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, 7 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 4 countries.

Adriana C CostaChongqing Key Laboratory of Colleges and Universities on Micro-Nano Systems Technology and Smart Transducing, Chongqing Engineering Laboratory for Detection, Institute of Applied Micro-Nano Science and Technology-IAMNST, Control and Integrated System, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Nan'an District,Chongqing 400067, China. adriana.c.costa@dei.uminho.pt.
Sara PimentaCMEMS-UMinho, Department of Industrial Electronics, University of Minho, 4800-058 Guimaraes, Portugal. sara.pimenta@dei.uminho.pt.
João F RibeiroCMEMS-UMinho, Department of Industrial Electronics, University of Minho, 4800-058 Guimaraes, Portugal. jribeiro@dei.uminho.pt.
Manuel F SilvaCMEMS-UMinho, Department of Industrial Electronics, University of Minho, 4800-058 Guimaraes, Portugal. fsilva@dei.uminho.pt.
Reinoud F WolffenbuttelFaculty of EEMCS, TUDelft, Mekelweg 4, 2628 CD Delft, The Netherlands. r.f.wolffenbuttel@tudelft.nl.
Tao DongChongqing Key Laboratory of Colleges and Universities on Micro-Nano Systems Technology and Smart Transducing, Chongqing Engineering Laboratory for Detection, Institute of Applied Micro-Nano Science and Technology-IAMNST, Control and Integrated System, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Nan'an District,Chongqing 400067, China. Tao.Dong@usn.no.
Zhaochu YangChongqing Key Laboratory of Colleges and Universities on Micro-Nano Systems Technology and Smart Transducing, Chongqing Engineering Laboratory for Detection, Institute of Applied Micro-Nano Science and Technology-IAMNST, Control and Integrated System, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Nan'an District,Chongqing 400067, China. Zhaochu.Yang@usn.no.
José H CorreiaChongqing Key Laboratory of Colleges and Universities on Micro-Nano Systems Technology and Smart Transducing, Chongqing Engineering Laboratory for Detection, Institute of Applied Micro-Nano Science and Technology-IAMNST, Control and Integrated System, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Nan'an District,Chongqing 400067, China. higino.correia@dei.uminho.pt.
Chongqing Technology and Business University · CNUniversity of Minho · PTDelft University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Minimally invasive medical devices can greatly benefit from Narrow Band Imaging (NBI) diagnostic capabilities, as different wavelengths allow penetration of distinct layers of the gastrointestinal tract mucosa, improving diagnostic accuracy and targeting different pathologies. An important performance parameter is the light intensity at a given power consumption of the medical device. A method to increase the illumination intensity in the NBI diagnostic technique was developed and applied to minimally invasive medical devices (e.g., endoscopic capsules), without increasing the size and power consumption of such instruments. Endoscopic capsules are generally equipped with light-emitting diodes (LEDs) operating in the RGB (red, green, and blue) visible light spectrum. A polydimethylsiloxane (PDMS) µ-lens was designed for a maximum light intensity at the target area of interest when placed on top of the LEDs. The PDMS µ-lens was fabricated using a low-cost hanging droplet method. Experiments reveal an increased illumination intensity by a factor of 1.21 for both the blue and green LEDs and 1.18 for the red LED. These promising results can increase the resolution of NBI in endoscopic capsules, which can contribute to early gastric lesions diagnosis.

Indexed as

LightNarrow Band ImagingDimethylpolysiloxanesbaysilonDimethylpolysiloxanesminimally invasive medical devicesNarrow Band Imaging (NBI)Polydimethylsiloxane (PDMS) µ-lens

Identifiers

PMID30832271
PMCPMC6427716
OpenAlexW2920775305

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.