Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
Immunofluorescence Microscopy01:12

Immunofluorescence Microscopy

A fluorescence microscope uses fluorescent chromophores called fluorochromes, which can absorb energy from a light source and then emit this energy as visible light. Fluorochromes include naturally fluorescent substances (such as chlorophylls) and fluorescent stains that are added to the specimen to create contrast. Dyes such as Texas red and FITC are examples of fluorochromes. Other examples include the nucleic acid dyes 4’,6’-diamidino-2-phenylindole (DAPI), and acridine orange.
The...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

"That is why I trust": a qualitative study on acceptability and feasibility of novel tongue swab diagnostics to assess people presenting with tuberculosis symptoms in Viet Nam and Zambia.

BMC health services research·2026
Same author

Reach, implementation fidelity, and safety of bubble continuous positive airway pressure (bCPAP) therapy in children with severe pneumonia in Pakistan.

PLOS global public health·2026
Same author

Multilevel factors associated with virological suppression among adolescents and young people with prior non-suppression receiving intensive adherence counselling in East-Central Uganda.

AIDS research and therapy·2026
Same author

A multi-omics study reveals pathway-level insights and predictive biomarkers in pediatric TB.

Clinical proteomics·2026
Same author

Effect of prior TB preventive therapy on all-cause mortality during TB treatment among people with HIV/TB in rural eastern Uganda: an observational causal analysis.

BMC infectious diseases·2026
Same author

Sputum scarcity and associated factors in people undergoing tuberculosis testing in South Africa, Uganda, India, and the Philippines: an analysis of cross-sectional observational data.

EClinicalMedicine·2026

Related Experiment Video

Updated: May 15, 2026

Imaging Mycobacterium tuberculosis in Mice with Reporter Enzyme Fluorescence
10:06

Imaging Mycobacterium tuberculosis in Mice with Reporter Enzyme Fluorescence

Published on: February 26, 2018

Automated tuberculosis diagnosis using fluorescence images from a mobile microscope.

Jeannette Chang1, Pablo Arbeláez, Neil Switz

  • 1UC Berkeley, Department of Electrical Engineering and Computer Sciences, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|January 5, 2013
PubMed
Summary

An automated algorithm accurately detects tuberculosis (TB) in sputum smear images using digital microscopy. This technology can improve TB diagnosis in remote areas lacking laboratory access.

More Related Videos

A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening
15:28

A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening

Published on: January 17, 2014

Related Experiment Videos

Last Updated: May 15, 2026

Imaging Mycobacterium tuberculosis in Mice with Reporter Enzyme Fluorescence
10:06

Imaging Mycobacterium tuberculosis in Mice with Reporter Enzyme Fluorescence

Published on: February 26, 2018

A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening
15:28

A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening

Published on: January 17, 2014

Area of Science:

  • Medical Diagnostics
  • Computer Vision
  • Public Health

Background:

  • Tuberculosis (TB) diagnosis in low-resource settings relies on manual sputum smear microscopy.
  • Limited access to laboratory diagnostics hinders effective TB detection in rural populations.
  • Digital microscopy offers a potential solution for decentralized TB diagnostics.

Purpose of the Study:

  • To develop and validate an automated algorithm for tuberculosis bacilli detection using digital microscopy images.
  • To assess the algorithm's performance in identifying TB in sputum smears from a low-resource setting.
  • To evaluate the potential of automated digital microscopy for improving global TB healthcare access.

Main Methods:

  • An automated algorithm employing morphological operations and template matching was developed.
  • Candidate TB objects were identified and characterized using Hu moments, geometric/photometric features, and histograms of oriented gradients.
  • Support vector machine classification was utilized for object-level and slide-level TB detection.
  • The algorithm was tested on 594 CellScope images from 290 patients in Uganda.

Main Results:

  • The automated algorithm achieved high object-level classification accuracy with an average precision of 89.2% +/- 2.1%.
  • Slide-level classification performance was comparable to that of human readers.
  • The study demonstrated the algorithm's effectiveness on real-world clinical data from a low-resource environment.

Conclusions:

  • Automated TB detection using digital microscopy is highly accurate and feasible.
  • This technology has the potential to significantly improve TB diagnosis accessibility in underserved regions.
  • The developed algorithm can aid in bringing essential healthcare services to rural communities, impacting global TB control efforts.