Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/16720
Título: Multi-focus image fusion for bacilli images in conventional sputum smear microscopy for tuberculosis
Autor: Costa, Marly Guimarães Fernandes
Pinto, K. M.B.
Fujimoto, Luciana Botinelly Mendonça
Ogusku, Maurício Morishi
Costa Filho, Cícero Ferreira Fernandes
Palavras-chave: Bacilli
Image Processing
Automatic Detection
Bright-field Microscopy
Depth Of Field
Diagnostic Methods
Light Fields
Multi-focus
Multifocus Image Fusion
Tuberculosis
Image Fusion
Bacilli
Bacterial Strain
Bright-field Microscopy
Color
Controlled Study
Human
Image Analysis
Image Processing
Kruskal Wallis Test
Multifocus Image Fusion
Preservation
Priority Journal
Sputum Smear
Tuberculosis
Variance
Wavelet Transformation
Data do documento: 2019
Revista: Biomedical Signal Processing and Control
É parte de: Volume 49, Pags. 289-297
Abstract: Bright-field microscopy of sputum samples is still the most widely used Tuberculosis (TB) diagnostic method in countries facing a high incidence of TB. However, this diagnostic method, because it is a visual analysis, requires attention and training of those who perform it, and presents high intra- and inter-observed variation. As a result, many research groups are working on methods of automatic detection of bacilli, aiming to automate this process. The fact that not all of the bacilli present in the examined microscope field are in focus increases the challenge faced by researchers in obtaining automatic methods of detecting bacilli. Fusion images can be a means of overcoming this problem, combining multiple images, from the same field, with diverse focuses into a single focused one. In this paper, we present a multi-focus image fusion method applied to conventional sputum smear microscopy images. The goal is to establish the best method to obtain an extended focus microscopy image where all bacilli present in the field are in focus. The proposed method was compared with three other techniques from the literature by using Variance and Multichannel QAB/F metrics. The proposed method exhibited the best balance of quality evidence (focus and preservation of information). © 2018
DOI: 10.1016/j.bspc.2018.12.018
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