Hyperspectral Imaging System for Tissue Classification in H&E-Stained Histological Slides

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Author(s):	Souza, Mateus Martelini ; Carvalho, Felipe Alvarenga ; Vanzela Sverzut, Enzo Fabro ; Requena, Michelle Barreto ; Garcia, Marlon Rodrigues ; Pratavieira, Sebastiao ; IEEE Total Authors: 7
Document type:	Journal article
Source:	2021 SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE (SBFOTON IOPC); v. N/A, p. 4-pg., 2021-01-01.
Abstract
This paper presents the development of a hyper-spectral imaging system for the classification of H&E-stained histological slides. The system was developed to be coupled to a conventional microscope, with software dedicated to control the instrumentation, to show a colorful live image from an RGB camera, and to acquire the hyperspectral imaging using a liquid crystal tunable filter (LCTF). Hyperspectral images of H&E-stained histological slides undergoing photodynamic therapy were classified with four machine learning algorithms to find damaged tissues (crust). The classification results were presented and show that this technique is promising to classify histological tissue regions. (AU)

FAPESP's process:	13/07276-1 - CEPOF - Optics and Photonic Research Center
Grantee:	Vanderlei Salvador Bagnato
Support Opportunities:	Research Grants - Research, Innovation and Dissemination Centers - RIDC


FAPESP's process:	14/50857-8 - National Institute in Basic Optics and Applied to Life Sciences
Grantee:	Vanderlei Salvador Bagnato
Support Opportunities:	Research Projects - Thematic Grants