Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pulmonary Tuberculosis IV

Pulmonary Tuberculosis IV

Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...

You might also read

Related Articles

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

Sort by

Same author

Structural Insights into the Glycosylphosphatidylinositol Mannosyltransferase I Complex from <i>Candida glabrata</i>.

Journal of fungi (Basel, Switzerland)·2025

Same author

Mixed-Dimensional Chiral COF-2D Molecular Crystal Heterojunctions for Neuromorphic Circular Polarization Vision.

Advanced materials (Deerfield Beach, Fla.)·2025

Same author

Mathematical modeling of tuberculosis with two strains, seasonality, and age heterogeneity.

Journal of theoretical biology·2025

Same author

Glutamate synaptic pathway plays an important role in neodymium oxide-incduced oxidative stress and inflammation of the brain.

Human & experimental toxicology·2025

Same author

Construction and evaluation of a risk prediction model for postoperative deep vein thrombosis in gynecological patients.

The journal of obstetrics and gynaecology research·2025

Same author

Spiking neural P systems with structural plasticity and weights.

Bio Systems·2025

Same journal

A novel SE-ResNet architecture for continuous estimation of wrist and hand movements from HD-sEMG.

Medical & biological engineering & computing·2026

Same journal

Anti-aliasing-enhanced WaveUNet for clinically reliable 12-lead ECG reconstruction from limited 3-lead input.

Medical & biological engineering & computing·2026

Same journal

Deep multi-modal features based spatio-temporal video regression for non-invasive hemoglobin estimation.

Medical & biological engineering & computing·2026

Same journal

Reduced mechanical strength correlates with decreased elastin content in aortic intima-media tissue: association with dissection in human ascending aortas.

Medical & biological engineering & computing·2026

Same journal

How plaque morphology and stenosis severity govern stent-artery interaction and deployment outcomes: a computational study.

Medical & biological engineering & computing·2026

Same journal

Investigating a relation between amyloid beta plaque burden and accumulated neurotoxicity caused by amyloid beta oligomers.

Medical & biological engineering & computing·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 13, 2025

Author Spotlight: Optimizing CFU Determination for Efficient Assessment of TB Vaccine Efficacy and Antigen Presentation Analysis

Author Spotlight: Optimizing CFU Determination for Efficient Assessment of TB Vaccine Efficacy and Antigen Presentation Analysis

Published on: July 28, 2023

Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.

Yonghong Li^1,2, Haiyang Qiu³, Sidong Xian²

¹School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China.

Medical & Biological Engineering & Computing

|September 12, 2024

Summary

This summary is machine-generated.

This study introduces Lite-YOLOv8, an optimized deep learning model for detecting Tubercle Bacilli in sputum samples. The new algorithm improves accuracy and significantly reduces model size, aiding deployment on medical devices.

Keywords:

Deep learning Model lightweight Small-objects detection Tubercle Bacilli YOLOv8

More Related Videos

A Tuberculosis Molecular Bacterial Load Assay TB-MBLA

A Tuberculosis Molecular Bacterial Load Assay TB-MBLA

Published on: April 30, 2020

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

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: Jun 13, 2025

Author Spotlight: Optimizing CFU Determination for Efficient Assessment of TB Vaccine Efficacy and Antigen Presentation Analysis

Author Spotlight: Optimizing CFU Determination for Efficient Assessment of TB Vaccine Efficacy and Antigen Presentation Analysis

Published on: July 28, 2023

A Tuberculosis Molecular Bacterial Load Assay TB-MBLA

A Tuberculosis Molecular Bacterial Load Assay TB-MBLA

Published on: April 30, 2020

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

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 imaging
Computer vision
Deep learning applications in healthcare

Background:

Manual detection of Tubercle Bacilli in sputum is time-consuming and prone to errors.
Complex backgrounds and small, numerous bacilli pose challenges for automated detection.

Purpose of the Study:

To develop a lightweight and accurate deep learning model for Tubercle Bacilli detection.
To optimize the YOLOv8s model for improved performance in medical diagnostics.

Main Methods:

Proposed Lite-YOLOv8 algorithm using Lite-C2f module and a lightweight down-sampling module.
Implemented NWD loss to address small object positional bias.
Evaluated performance on public Tubercle Bacilli datasets.

Main Results:

Achieved 86.3% mean average precision (mAP), outperforming YOLOv8s.
Improved mAP0.5 by 2.2%, precision by 1.5%, and recall by 2.8%.
Reduced model parameters from 11.2M to 5.1M and GFLOPs from 28.8 to 13.8.

Conclusions:

Lite-YOLOv8 offers a more accurate and lightweight solution for Tubercle Bacilli detection.
The model's efficiency facilitates deployment on resource-constrained medical devices.
Enhances convenience and accuracy for medical professionals in diagnosing tuberculosis.