TY - GEN
T1 - Classification and Counting of Mycobacterium Tuberculosis from Sputum Microscopic Image using Fuzzy Logic
AU - Ade Pangestu, Nilam
AU - Sigit, Riyanto
AU - Harsono, Tri
AU - Retno Wahyunitisari, Manik
AU - Anwar, Anwar
AU - Ayu Yunitasari, Dinda
N1 - Funding Information:
Comparing nm, upconversion luminescence intensity of the 2:1 type compound is stronger than that of the 5:1 type compound. This demonstrates that upconversion luminescence intensity of the compounds made up of CsCl and EuCl This work was supported by tie National Natural Science Foundation of China, which is gratefully acknowledged. The authors acknowledge the help of Prof. Xia Shu-Ping of Qing-Hai Salt Lake institute of Academy of Sciences in China. figure 5b with figure 6b , the result shows that, when excited at the same 790 3 will also increase with the increasing of Eu 3+ in CsCl. The luminescence mechanism of the two compounds and the effect of the crystal field on the luminescence property and signal crystal structure will be discussed elsewhere.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - The diagnosis of tuberculosis (TB) is done by detecting and counting the number of mycobacterium tuberculosis in a sputum examination done manually using a microscope. It is considered ineffective because it requires a long time and different diagnostic results. To overcome this problem, this paper implements digital image processing. There are 5 processes used on the system. Preprocessing with the RGB to HSV method is used to clarify the color of the image. Segmentation to separate objects from background images using thresholding. Feature extraction to get the value of area, perimeter, and level of roundness of the object. Classification uses fuzzy logic to classify mycobacterium tuberculosis based on features. The next is the process of counting mycobacterium tuberculosis. And the last is the process of classify into IUATLD scale based on the number of mycobacterium tuberculosis. From the results of tests conducted on 15 data, the system show that the level of accuracy, precision, sensitivity and specificity of system in calculate mycobacterium tuberculosis is 89%, 90%, 91.66% and 78.88% respectively. And also level of sensitivity, specificity and accuracy of system in classifying the level of infection is 100%, 80 % and 93% respectively. This system was tested on a microscopic sputum image database of RSUD Dr. Soetomo from a different patient.
AB - The diagnosis of tuberculosis (TB) is done by detecting and counting the number of mycobacterium tuberculosis in a sputum examination done manually using a microscope. It is considered ineffective because it requires a long time and different diagnostic results. To overcome this problem, this paper implements digital image processing. There are 5 processes used on the system. Preprocessing with the RGB to HSV method is used to clarify the color of the image. Segmentation to separate objects from background images using thresholding. Feature extraction to get the value of area, perimeter, and level of roundness of the object. Classification uses fuzzy logic to classify mycobacterium tuberculosis based on features. The next is the process of counting mycobacterium tuberculosis. And the last is the process of classify into IUATLD scale based on the number of mycobacterium tuberculosis. From the results of tests conducted on 15 data, the system show that the level of accuracy, precision, sensitivity and specificity of system in calculate mycobacterium tuberculosis is 89%, 90%, 91.66% and 78.88% respectively. And also level of sensitivity, specificity and accuracy of system in classifying the level of infection is 100%, 80 % and 93% respectively. This system was tested on a microscopic sputum image database of RSUD Dr. Soetomo from a different patient.
KW - counting bacilli
KW - fuzzy logic
KW - mycobacterium tuberculosis
KW - segmentation
KW - sputum microscopic image
UR - http://www.scopus.com/inward/record.url?scp=85096749719&partnerID=8YFLogxK
U2 - 10.1109/IES50839.2020.9231925
DO - 10.1109/IES50839.2020.9231925
M3 - Conference contribution
AN - SCOPUS:85096749719
T3 - IES 2020 - International Electronics Symposium: The Role of Autonomous and Intelligent Systems for Human Life and Comfort
SP - 520
EP - 526
BT - IES 2020 - International Electronics Symposium
A2 - Yunanto, Andhik Ampuh
A2 - Hermawan, Hendhi
A2 - Mu'arifin, Mu'arifin
A2 - Muliawati, Tri Hadiah
A2 - Putra, Putu Agus Mahadi
A2 - Gamar, Farida
A2 - Ridwan, Mohamad
A2 - Kusuma N, Artiarini
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Electronics Symposium, IES 2020
Y2 - 29 September 2020 through 30 September 2020
ER -
