Evidence map›Paper›PMID 35591109›Full record

ArticleSensors (Basel, Switzerland)2022

FPI Based Hyperspectral Imager for the Complex Surfaces-Calibration, Illumination and Applications.

Anna-Maria Raita-Hakola, Leevi Annala, Vivian Lindholm, Roberts Trops, Antti Näsilä, Heikki Saari, Annamari Ranki, Ilkka Pölönen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. 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.

Anna-Maria Raita-HakolaFaculty of Information Technology, University of Jyväskylä, 40100 Jyväskylä, Finland.ORCID 0000-0002-5984-609X
Leevi AnnalaFaculty of Information Technology, University of Jyväskylä, 40100 Jyväskylä, Finland.ORCID 0000-0002-8297-8859
Vivian LindholmDepartment of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland.ORCID 0000-0003-2707-0861
Roberts TropsVTT Technical Research Centre of Finland Ltd., 02150 Espoo, Finland.
Antti NäsiläVTT Technical Research Centre of Finland Ltd., 02150 Espoo, Finland.
Heikki SaariVTT Technical Research Centre of Finland Ltd., 02150 Espoo, Finland.ORCID 0000-0003-3038-7122
Annamari RankiDepartment of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland.ORCID 0000-0003-4335-0396
Ilkka PölönenFaculty of Information Technology, University of Jyväskylä, 40100 Jyväskylä, Finland.ORCID 0000-0002-5129-7364

Funding

Academy of Finland 314519Academy of Finland 314520Academy of Finland 314521
6 · The paper itself

Abstract

Hyperspectral imaging (HSI) applications for biomedical imaging and dermatological applications have been recently under research interest. Medical HSI applications are non-invasive methods with high spatial and spectral resolution. HS imaging can be used to delineate malignant tumours, detect invasions, and classify lesion types. Typical challenges of these applications relate to complex skin surfaces, leaving some skin areas unreachable. In this study, we introduce a novel spectral imaging concept and conduct a clinical pre-test, the findings of which can be used to develop the concept towards a clinical application. The SICSURFIS spectral imager concept combines a piezo-actuated Fabry-Pérot interferometer (FPI) based hyperspectral imager, a specially designed LED module and several sizes of stray light protection cones for reaching and adapting to the complex skin surfaces. The imager is designed for the needs of photometric stereo imaging for providing the skin surface models (3D) for each captured wavelength. The captured HS images contained 33 selected wavelengths (ranging from 477 nm to 891 nm), which were captured simultaneously with accordingly selected LEDs and three specific angles of light. The pre-test results show that the data collected with the new SICSURFIS imager enable the use of the spectral and spatial domains with surface model information. The imager can reach complex skin surfaces. Healthy skin, basal cell carcinomas and intradermal nevi lesions were classified and delineated pixel-wise with promising results, but further studies are needed. The results were obtained with a convolutional neural network.

Indexed as

Hyperspectral ImagingLightingCalibrationDiagnostic ImagingNeural Networks, Computerbiomedical imagingcalibrationconvolutional neural networkdermatological applicationFPIhyperspectralinterferometryLED illuminationoptical biopsyoptical modellingphotometric stereoskin surface model

Identifiers

PMID35591109
PMCPMC9103796

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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.