Literature DB >> 33210464

Hyperspectral imaging as a diagnostic tool to differentiate between amalgam tattoos and other dark pigmented intraoral lesions.

Johannes Laimer1, Emanuel Bruckmoser2, Tom Helten1, Barbara Kofler3, Bettina Zelger4, Andrea Brunner4, Bernhard Zelger5, Christian W Huck6, Michelle Tappert7, Derek Rogge7, Michael Schirmer8, Johannes D Pallua4,9.   

Abstract

The goal of this project is to identify any in-depth benefits and drawbacks in the diagnosis of amalgam tattoos and other pigmented intraoral lesions using hyperspectral imagery collected from amalgam tattoos, benign, and malignant melanocytic neoplasms. Software solutions capable of classifying pigmented lesions of the skin already exist, but conventional red, green and blue images may be reaching an upper limit in their performance. Emerging technologies, such as hyperspectral imaging (HSI) utilize more than a hundred, continuous data channels, while also collecting data in the infrared. A total of 18 paraffin-embedded human tissue specimens of dark pigmented intraoral lesions (including the lip) were analyzed using visible and near-infrared (VIS-NIR) hyperspectral imagery obtained from HE-stained histopathological slides. Transmittance data were collected between 450 and 900 nm using a snapshot camera mounted to a microscope with a halogen light source. VIS-NIR spectra collected from different specimens, such as melanocytic cells and other tissues (eg, epithelium), produced distinct and diagnostic spectra that were used to identify these materials in several regions of interest, making it possible to distinguish between intraoral amalgam tattoos (intramucosal metallic foreign bodies) and melanocytic lesions of the intraoral mucosa and the lip (each with P < .01 using the independent t test). HSI is presented as a diagnostic tool for the rapidly growing field of digital pathology. In this preliminary study, amalgam tattoos were reliably differentiated from melanocytic lesions of the oral cavity and the lip.
© 2020 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.

Entities:  

Keywords:  amalgam; hyperspectral microscopic imaging; intraoral lesions

Mesh:

Year:  2020        PMID: 33210464     DOI: 10.1002/jbio.202000424

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  1 in total

1.  Effective band selection of hyperspectral image by an attention mechanism-based convolutional network.

Authors:  Zengwei Zheng; Yi Liu; Mengzhu He; Dan Chen; Lin Sun; Fengle Zhu
Journal:  RSC Adv       Date:  2022-03-21       Impact factor: 3.361

  1 in total

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