skip to main content
Visitante
Meu Espaço
Minha Conta
Sair
Identificação
This feature requires javascript
Tags
Revistas Eletrônicas (eJournals)
Livros Eletrônicos (eBooks)
Bases de Dados
Bibliotecas USP
Ajuda
Ajuda
Idioma:
Inglês
Espanhol
Português
This feature required javascript
This feature requires javascript
Primo Search
Busca Geral
Busca Geral
Acervo Físico
Acervo Físico
Produção Intelectual da USP
Produção USP
Search For:
Clear Search Box
Search in:
Busca Geral
Or hit Enter to replace search target
Or select another collection:
Search in:
Busca Geral
Busca Avançada
Busca por Índices
This feature requires javascript
This feature requires javascript
Adaptive fusion of bright-field microscopy images acquired in different focal planes
Catanante, Victor Augusto Alves
Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Ciências Matemáticas e de Computação 2020-07-10
Acesso online
Exibir Online
Detalhes
Resenhas & Tags
Mais Opções
This feature requires javascript
Enviar para
Adicionar ao Meu Espaço
Remover do Meu Espaço
E-mail (máximo 30 registros por vez)
Imprimir
Link permanente
Referência
EasyBib
EndNote
RefWorks
del.icio.us
Exportar RIS
Exportar BibTeX
This feature requires javascript
Título:
Adaptive fusion of bright-field microscopy images acquired in different focal planes
Autor:
Catanante, Victor Augusto Alves
Orientador:
Batista Neto, João do Espírito Santo; Bruno, Odemir Martinez
Assuntos:
Avaliação De Qualidade De Imagem Sem Referência
;
Microscopia De Campo Claro
;
Laplaciano Da Gaussiana
;
Fusão De Imagens Multifocais
;
Transformada Discreta De Fourier
;
Laplacian Of Gaussian
;
Discrete Fourier Transform
;
Bright-Field Microscopy
;
Multi-Focus Image Fusion
;
No-Reference Image Quality Assessment
Notas:
Dissertação (Mestrado)
Descrição:
Microscopy is an extremely relevant technique related to tasks that deal with micrometric order structures. Its use dates back to the 17th century and tends to evolve in parallel with the evolution of human technological knowledge. Among the various applications, the fields of biological and health sciences stand out, which involve structures normally invisible to the naked eye. There are unavoidable differences in depth between the points of the surfaces and structures which yield out-of-focus blur to images. However, high quality is necessary in order to allow precise analysis in microscopy applications. In this sense, image quality assessment and image fusion are examples of techniques that may be applied to solve the issue. Recent works on such fields show that mathematical techniques such as frequency domain analysis, multiresolution analysis and convolutional neural networks are effective to quantitatively assess the quality of images. At the same time, researchers also present many novel techniques for image fusion, either based on classical tools such as edge detection or based on state-of-the-art machine learning frameworks. The aim of this work is to develop a two-stage method, consisting of a no-reference image quality assessment and an image fusion step, to perform the fusion of bright-field light microscopy images acquired in different focal planes, and propose novel bright-field microscopy image datasets of plant leaf histological samples as a benchmark for testing both quality assessment and fusion algorithms. Frequency domain analysis and statistical methods were used to obtain a quality metric and the energy of edges extracted with the Laplacian of Gaussian filter as the fusion rule. The mean Pearsons correlation coefficient obtained for the image quality method was 0.7448, while the mean spatial frequency for the image fusion method was 0.0667.
DOI:
10.11606/D.55.2020.tde-10092020-164245
Editor:
Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Ciências Matemáticas e de Computação
Data de criação/publicação:
2020-07-10
Formato:
Adobe PDF
Idioma:
Inglês
Links
Este item no Dedalus
Teses e Dissertações USP
E-mail do autor
E-mail do orientador
E-mail do orientador
This feature requires javascript
This feature requires javascript
Voltar para lista de resultados
This feature requires javascript
This feature requires javascript
Buscando em bases de dados remotas. Favor aguardar.
Buscando por
em
scope:(USP_VIDEOS),scope:("PRIMO"),scope:(USP_FISICO),scope:(USP_EREVISTAS),scope:(USP),scope:(USP_EBOOKS),scope:(USP_PRODUCAO),primo_central_multiple_fe
Mostrar o que foi encontrado até o momento
This feature requires javascript
This feature requires javascript