Title:Recent Advances in Analysis and Detection of Tuberculosis System in
Chest X-Ray Using Artificial Intelligence (AI) Techniques: A Review
Volume: 16
Issue: 1
Author(s): Shanmugam Suchitra, S. Jafar Ali Ibrahim*, Mariappan Sathya, Varsha Sahini, N. Surya Kalyan Chakravarthy, Vaneet Kumar* Saruchi
Affiliation:
- Department of IOT, SCOPE, Vellore Institute of Technology, Vellore, Tamilnadu, India
- Department of Applied Sciences, CT Institute of Engineering, Management
and Technology, Shahpur Campus Jalandhar, Punjab, India
Keywords:
Tuberculosis, artificial intelligence, machine learning, deep learning, chest x-rays, computer vision, computer-aided detection, diagnosis system.
Abstract: Mycobacterium tuberculosis causes tuberculosis (TB), a bacterial illness. Although
germs are most typically found in the lungs, they can affect other sections of the body as well.
Tuberculosis is one of the primary causes of mortality in both developed and developing nations,
necessitating worldwide attention. Even though TB may be prevented in the majority of instances
if discovered and treated early, the number of deaths caused by the disease is quite high. There
has been a significant increase in interest and research activity in TB detection in recent years.
The new advancement in the field of AI Technology may be able to assist them in overcoming
these development gaps. Computer-Aided Detection and Diagnosis (CADD) aids in the diagnosis
of diseases by analysing symptoms and X-ray images of patients. Many solutions are currently being
developed to improve the effectiveness of TB diagnosis classification using AI and DL approaches.
Although a variety of TB detection techniques have been developed, there is no commonly
acknowledged method. The purpose of this study is to give a survey on Tuberculosis Detection.
It also emphasises the difficulty and complexity of the Tuberculosis Detection System's design.
