Integration of Microscopic Image Capturing System for Automatic
Detection of Mycobacterium Tuberculosis Bacteria
Dublin Core
Title
Integration of Microscopic Image Capturing System for Automatic
Detection of Mycobacterium Tuberculosis Bacteria
Detection of Mycobacterium Tuberculosis Bacteria
Subject
tuberculosis; sputum; image processing; microscope
Description
he Ministry of Health of the Republic of Indonesia is running a program to eliminate Tuberculosis (TB) by 2030.
At the Primary Health Care level, AFB (acid-fast bacteria) examination confirms the TB diagnosis. In this process,
the patient's sputum is prepared in the form of preparation and observed by the laboratory analyst through the
lens of a microscope. The reporting process to establish this diagnosis requires calculating the number of TB
bacteria in 100 fields of view per preparation. This manual microscopic observation process is tedious, and the
reading results are subjective. This study offers an integrated design for automatic microscopic imaging with a
computer-integrated TB bacteria detection system. The process of taking pictures is automatically obtained with
the help of a driving motor added to the microscope. With the addition of this motor, the process of taking
microscopic images for 100 fields of view takes ±450 seconds. The proposed system integration process can reduce
laboratory analysts' work fatigue in conducting microscopic observations manually. The TB bacteria detection
system utilizes the working principle of image processing techniques by combining color-deconvolution,
segmentation, and contour-detection methods. The comparative value of the TB object detection system with
experts resulted in a sensitivity value of 77% and a specificity value of 68%. However, the low detection rate is
because the image obtained is still blurry. Thus, further investigation is needed to determine the driving motor's
movement rate and the right timing for taking microscopic images so that the resulting image is not blurry. The
final result that is the focus of this paper is the successful integration of the system carried out between the motor
drive system on the preparation stand and the TB bacteria detection system to become a unified system.
At the Primary Health Care level, AFB (acid-fast bacteria) examination confirms the TB diagnosis. In this process,
the patient's sputum is prepared in the form of preparation and observed by the laboratory analyst through the
lens of a microscope. The reporting process to establish this diagnosis requires calculating the number of TB
bacteria in 100 fields of view per preparation. This manual microscopic observation process is tedious, and the
reading results are subjective. This study offers an integrated design for automatic microscopic imaging with a
computer-integrated TB bacteria detection system. The process of taking pictures is automatically obtained with
the help of a driving motor added to the microscope. With the addition of this motor, the process of taking
microscopic images for 100 fields of view takes ±450 seconds. The proposed system integration process can reduce
laboratory analysts' work fatigue in conducting microscopic observations manually. The TB bacteria detection
system utilizes the working principle of image processing techniques by combining color-deconvolution,
segmentation, and contour-detection methods. The comparative value of the TB object detection system with
experts resulted in a sensitivity value of 77% and a specificity value of 68%. However, the low detection rate is
because the image obtained is still blurry. Thus, further investigation is needed to determine the driving motor's
movement rate and the right timing for taking microscopic images so that the resulting image is not blurry. The
final result that is the focus of this paper is the successful integration of the system carried out between the motor
drive system on the preparation stand and the TB bacteria detection system to become a unified system.
Creator
Agus Darmawan1
, Izzati Muhimmah2*, Rahadian Kurniawan3
, Izzati Muhimmah2*, Rahadian Kurniawan3
Publisher
Universitas Islam Indonesia
Date
26-03-2023
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Agus Darmawan1
, Izzati Muhimmah2*, Rahadian Kurniawan3, “Integration of Microscopic Image Capturing System for Automatic
Detection of Mycobacterium Tuberculosis Bacteria,” Repository Horizon University Indonesia, accessed June 28, 2025, https://repository.horizon.ac.id/items/show/9359.
Detection of Mycobacterium Tuberculosis Bacteria,” Repository Horizon University Indonesia, accessed June 28, 2025, https://repository.horizon.ac.id/items/show/9359.