Literature DB >> 18002748

Evaluation of autofocus algorithms for tuberculosis microscopy.

Megan J Russell1, Tania S Douglas.   

Abstract

Direct sputum smear microscopy is the most cost-effective method of screening suspected cases of tuberculosis (TB) in high-prevalence countries. Automated microscopy of sputum smears to detect TB would enable rapid screening of large numbers of samples. We evaluate autofocus algorithms for TB microscopy as a step in the development of an automated microscope. Three different focus measures (namely the energy of the image Laplacian, the variance of the log-histogram and the first order Gaussian derivative) are tested on sequences of images of sputum smear slides with varying degrees of content density. A combination of search methods is applied in conjunction with the focus measure to find the position of optimal focus.

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Year:  2007        PMID: 18002748     DOI: 10.1109/IEMBS.2007.4353082

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

Review 1.  A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images.

Authors:  Rani Oomman Panicker; Biju Soman; Gagan Saini; Jeny Rajan
Journal:  J Med Syst       Date:  2015-10-30       Impact factor: 4.460

2.  Parallel implementations to accelerate the autofocus process in microscopy applications.

Authors:  Juan C Valdiviezo-N; Francisco J Hernandez-Lopez; Carina Toxqui-Quitl
Journal:  J Med Imaging (Bellingham)       Date:  2020-01-17

3.  Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model.

Authors:  Olfa Hrizi; Karim Gasmi; Ibtihel Ben Ltaifa; Hamoud Alshammari; Hanen Karamti; Moez Krichen; Lassaad Ben Ammar; Mahmood A Mahmood
Journal:  J Healthc Eng       Date:  2022-03-21       Impact factor: 3.822

4.  Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

Authors:  Declan O'Loughlin; Bárbara L Oliveira; Muhammad Adnan Elahi; Martin Glavin; Edward Jones; Milica Popović; Martin O'Halloran
Journal:  Sensors (Basel)       Date:  2017-12-06       Impact factor: 3.576

  4 in total

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