| Issue |
E3S Web Conf.
Volume 448, 2023
The 8th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2023)
|
|
|---|---|---|
| Article Number | 02052 | |
| Number of page(s) | 10 | |
| Section | Information System | |
| DOI | https://doi.org/10.1051/e3sconf/202344802052 | |
| Published online | 17 November 2023 | |
Effectiveness of Automatic Detection of Osteoarthritis using Convolutional Neural Network (CNN) Method with DenseNet201 on Digital Images of Knee Joint Radiography
1 Postgraduate Program Master in Applied Diagnostic Imaging, Poltekkes Kemenkes Semarang, Jalan Tirto Agung, Pedalangan, Banyumanik, Kota Semarang, 50239, Jawa Tengah, Indonesia.
2 Departement of Radiology, Kariadi Hospital, Jalan Dr. Sutomo No.16, Randusari, Semarang Selatan, Kota Semarang, 50244, Jawa Tengah, Indonesia
3 Stikes Siti Hajar, Jalan Letjend. Djamin Ginting, Padang Bulan, Kota Meden, 20222, Sumatra Utara, Indonesia
* Corresponding author: deanurfadhillah01@email.com
The manual detection of osteoarthritis using Kellgren Lawrence system depends on experience and agreement between doctors. The study was conducted to develop DenseNet201 to assist doctors in making a diagnosis of osteoarthritis grading. This study analyzes the accuracy; sensitivity; specificity; positive predictive value (PPV) and negative predictive value (NPV) of DenseNet201 in grading osteoarthritis and compares the classification results between DenseNet201 and radiologists in detecting osteoarthritis on knee joint images. This study is an applied experiment that compares the classification results of DenseNet201 and radiology specialists. Firstly, DenseNet201 is built with the MATLAB R2021a. Tests are carried out by measuring accuracy, sensitivity, specificity, PPV and NPV of 75 images of knee joint. Lastly, the data is analyzed using the Wilcoxon statistical test. The study has shown that the performance of DenseNet201 was good in detecting osteoarthritis, with accuracy value 91.84%; sensitivity value 76.61%; specificity value 94.32%; PPV 82.60% and NPV 94.32%. There was no significant difference between classification results using DenseNet201 and radiologist with a value (p>0.05) of 0.119. DenseNet201 can be considered as an alternative diagnostic tool for osteoarthritis with the condition that verification of the diagnostic decision still refers to the confirmation and justification of the radiologist.
Key words: Osteoarthritis / Knee Joint / DenseNet201
© The Authors, published by EDP Sciences, 2023
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