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Related Concept Videos

Pulmonary Tuberculosis I01:29

Pulmonary Tuberculosis I

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Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
Mode of...
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Pulmonary Tuberculosis II01:28

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Tuberculosis, or TB, is a bacterial infectious disease caused by Mycobacterium tuberculosis. While its primary impact is on the lungs, leading to pulmonary tuberculosis, it can also affect various other organs, a condition referred to as extrapulmonary tuberculosis.
Here is a detailed explanation of its pathophysiology:
Transmission: The process begins when a person inhales droplet nuclei containing M. tuberculosis. These are typically released into the air when an individual with pulmonary or...
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Pulmonary Tuberculosis V01:28

Pulmonary Tuberculosis V

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Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the...
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Effects of EDTA on End-Point Detection Methods01:18

Effects of EDTA on End-Point Detection Methods

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Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
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Pulmonary Tuberculosis III01:31

Pulmonary Tuberculosis III

988
Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:
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Pulmonary Tuberculosis IV01:26

Pulmonary Tuberculosis IV

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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...
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Automated Mycobacterium tuberculosis Detection in Multivariant Digitized Ziehl-Neelsen Staining Using Faster R-CNN

Riries Rulaningtyas1, Fashalli Giovi Bilhaq1, Deby Kusumaningrum2,3,4

  • 1Biomedical Engineering Study Program, Department of Physics, Faculty of Science and Technology, Universitas Airlangga, Surabaya, East Java, Indonesia, unair.ac.id.

International Journal of Biomedical Imaging
|January 23, 2026
PubMed
Summary
This summary is machine-generated.

This study developed an automated system for detecting tuberculosis (TB) bacteria using deep learning. The AI model achieved high accuracy, aiding in faster and more reliable TB diagnosis.

Keywords:
Faster R-CNNZiehl–Neelsenmultivariantsputum smeartuberculosis

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Area of Science:

  • Medical Diagnostics
  • Computer Science
  • Infectious Diseases

Background:

  • Tuberculosis (TB) remains a significant public health issue, especially in Indonesia.
  • Microscopic examination of sputum smears via Ziehl-Neelsen staining is a common TB diagnostic method.
  • Manual TB detection faces challenges due to staining variations and subjectivity.

Purpose of the Study:

  • To develop an automated system for detecting tuberculosis bacteria.
  • To leverage deep learning, specifically the Faster R-CNN algorithm with ResNet-50, for TB detection.

Main Methods:

  • Utilized the Faster R-CNN algorithm with ResNet-50 architecture.
  • Implemented the system using Python and the TensorFlow Object Detection API.
  • Applied data augmentation techniques including rotation, flipping, and color processing.

Main Results:

  • Achieved 88% accuracy, 94% precision, 93% recall, and 94% F1-score.
  • The model successfully outputs annotated images pinpointing TB bacteria locations.
  • Demonstrated the effectiveness of the automated system in identifying TB bacteria.

Conclusions:

  • Deep learning offers a promising approach for automating TB detection.
  • The developed system can assist medical professionals in TB diagnosis, especially in resource-limited settings.
  • Automated TB detection can improve diagnostic efficiency and reliability.