Evidence map›Paper›PMID 37050624›Full record

ArticleSensors (Basel, Switzerland)2023

A Novel Transmittance Vis-NIR Hyper-Spectral Imaging Scanner for Analysis of Photographic Negatives: A Potential Tool for Photography Conservation.

Costanza Cucci, Andrea Casini, Lorenzo Stefani, Barbara Cattaneo, Marcello Picollo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Costanza CucciInstitute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy.ORCID 0000-0001-8534-7465
Andrea CasiniInstitute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy.
Lorenzo StefaniInstitute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy.
Barbara CattaneoInstitute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy.ORCID 0000-0003-1986-256X
Marcello PicolloInstitute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy.ORCID 0000-0003-1012-6048

Funding

Regione Toscana Resolution N. 1091 2018, Tuscany region
6 · The paper itself

Abstract

This work illustrates a novel prototype of a transmittance hyperspectral imaging (HSI) scanner, operating in the 400-900 nm range, and designed on purpose for non-invasive analysis of photographic materials, such as negatives, films and slides. The instrument provides high-quality spectral data and high-definition spectral images on targets of small size (e.g., 35 mm film strips) and is the first example of HSI instrumentation specifically designed for applications in the photographic conservation field. The instrument was tested in laboratory and on a set of specimens selected from a damaged photographic archive. This experimentation, though preliminary, demonstrated the soundness of a technical approach based on HSI for large-scale spectroscopic characterization of photographic archival materials. The obtained results encourage the continuation of experimentation of HSI as an advanced tool for photography conservation.

Indexed as

imaging spectroscopynon-invasive analysisphotographic heritage conservationphotographic negativestransmittance hyperspectral imagingVis–NIR spectroscopy

Identifiers

PMID37050624
PMCPMC10098514

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.