Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/50652
Type: Artigo de Periódico
Title: Canine mammary cancer diagnosis from quantitative properties of nonlinear optical images
Authors: Luana Aparecida dos Reis
Ana Paula Vargas Garcia
Egleidson Frederik do Amaral Gomes
Francis G. J. Longford
Jeremy Graham Frey
Geovanni Dantas Cassali
Ana Maria de Paula
Abstract: We present nonlinear microscopy imaging results and analysis from canine mammary cancer biopsies. Second harmonic generation imaging allows information of the collagen structure in the extracellular matrix that together with the fluorescence of the cell regions of the biopsies form a base for comprehensive image analysis. We demonstrate an automated image analysis method to classify the histological type of canine mammary cancer using a range of parameters extracted from the images. The software developed for image processing and analysis allows for the extraction of the collagen fibre network and the cell regions of the images. Thus, the tissue properties are obtained after the segmentation of the image and the metrics are measured specifically for the collagen and the cell regions. A linear discriminant analysis including all the extracted metrics allowed to clearly separate between the healthy and cancerous tissue with a 91%-accuracy. Also, a 61%-accuracy was achieved for a comparison of healthy and three histological cancer subtypes studied.
Subject: Microscopia
Câncer
Óptica não-linear
language: eng
metadata.dc.publisher.country: Brasil
Publisher: Universidade Federal de Minas Gerais
Publisher Initials: UFMG
metadata.dc.publisher.department: ICX - DEPARTAMENTO DE FÍSICA
Rights: Acesso Aberto
metadata.dc.identifier.doi: https://doi.org/10.1364/BOE.400871
URI: http://hdl.handle.net/1843/50652
Issue Date: 2020
metadata.dc.url.externa: https://opg.optica.org/boe/fulltext.cfm?uri=boe-11-11-6413&id=441702
Appears in Collections:Artigo de Periódico

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