Detection of pneumonia from pediatric chest X-ray images by transfer learning

Yıl 2023, Cilt: 41 Sayı: 6, 1264 - 1271, 29.12.2023

Yasin Demir Özkan Bingöl

Öz

When pathogens such as viruses, bacteria and fungi attack the lungs, the alveoli fill with in-flamed fluid, causing pneumonia. Early diagnosis of this disease, which has fatal outcomes especially in children under 5 years old, is very important in controlling undesirable situa-tions. Chest X-ray images play an important role in the diagnosis of pneumonia. In addition, the fact that the amount of radiation is lower than imaging devices such as tomography and the possibility of being accessible even from rural areas creates an advantage for X-ray devices. However, X-ray images that are not always clear or human conditions such as fatigue and lack of attention can make it difficult for specialists to detect pneumonia. In this study, a transfer learning-based convolutional neural network (CNN) approach is proposed, which can help specialists in the early and accurate diagnosis of pneumonia in children and, classify healthy and diseased individuals through Chest X-ray images. As a result of the study, an original CNN was proposed by adding additional layers to the AlexNet architecture layers and a test accuracy of 96.31% was obtained.

Anahtar Kelimeler

CNN, Chest X-Ray Images, Pediatric Pneumonia, Transfer Learning

Kaynakça

• REFERENCES
• [1] Rudan I. Epidemiology and Etiology of Childhood Pneumonia. Bull World Health Organ 2008;86:408–416. [CrossRef]
• [2] URL-1. National Center for Biotechnology Information. Available at: https://www.ncbi.nlm.nih.gov/books/NBK536940/. Published Nov 21, 2020. Accessed on Dec 14, 2023.
• [3] Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health 2020;25:278. [CrossRef]
• [4] URL-2. World Health Organization. Available at: https://www.who.int/news-room/fact-sheets/detail/pneumonia. Published 2021 Feb 6. Accessed on Dec 14, 2023.
• [5] Aydogdu M, Ozyilmaz E, Aksoy H, Gursel G, Ekim N. Mortality prediction in community-acquired pneumonia requiring mechanical ventilation; values of pneumonia and intensive care unit severity scores. Tuberk Toraks 2010;58:25–34.
• [6] Toikka P, Virkki R, Mertsola J, Ashorn P, Eskola J, Ruuskanen O. Bacteremic pneumococcal pneumonia in children. Clin Infect Dis 1999;29:568–572. [CrossRef]
• [7] Toğaçar M, Ergen B, Sertkaya ME. Zatürre Hastalığının Derin Öğrenme Modeli ile Tespiti. Firat Univ J Eng 2019;31.
• [8] Gaál G, Maga B, Lukács A. Attention u-net based adversarial architectures for chest x-ray lung segmentation. arXiv preprint arXiv:2003.10304. 2020.
• [9] Rand T. A Radiologic approach to Diseases of the Chest. Eur J Radiol 1997;3:251–252. [CrossRef]
• [10] Rajpurkar P, Irvin J, Zhu K, Yang B, Mehta H, Duan T, et al. Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning. arXiv preprint arXiv:1711.05225. 2017.
• [11] Ayan E, Karabulut B, Ünver HM. Diagnosis of Pediatric Pneumonia with Ensemble of Deep Convolutional Neural Networks in Chest X-ray Images. Arabian J Sci Eng 2021;1–17. [CrossRef]
• [12] Bozkurt F, Bayram E. Local Binary Pattern Based COVID-19 Detection Method Using Chest X-Ray Images. 2021 29th Signal Processing and Communications Applications Conference (SIU). 2021:1–4. [CrossRef]
• [13] Dey N, Zhang YD, Rajinikanth V, Pugalenthi R, Raja NSM. Customized VGG19 architecture for pneumonia detection in chest X-rays. Pattern Recognit Lett 2021;143:67–74. [CrossRef]
• [14] Kundu R, Das R, Geem ZW, Han GT, Sarkar R. Pneumonia detection in chest X-ray images using an ensemble of deep learning models. PLoS One 2021;16. [CrossRef]
• [15] Han Y, Chen C, Tewfik A, Ding Y, Peng Y. Pneumonia detection on chest x-ray using radiomic features and contrastive learning. Proc IEEE Int Symp Biomed Imaging 2021;2021:247–251. [CrossRef]
• [16] Mooney P. Chest X-Ray Images (Pneumonia). Available at: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. Published 2018 Mar 24. Accessed on Dec 14, 2023.
• [17] Gülgün OD, Erol Prof Dr H. Classification Performance Comparisons of Deep Learning Models In Pneumonia Diagnosis Using Chest X-Ray Images. Turk J Eng 2019;4:129–141. [CrossRef]
• [18] Hidayatullah RC, Violina S. Convolutional Neural Network Architecture and Data Augmentation for Pneumonia Classification from Chest X-Rays Images. Int J Innov Sci Res Technol 2020;5:7.
• [19] Demir Y, Bingöl Ö. Evrişimsel Sinir Ağı Yöntemi ile Pediatrik Akciğer Röntgen Görüntülerinden Pnömoni Tespiti. In: 2021 29th Signal Processing and Communications Applications Conference (SIU 2021). IEEE. 2021:1–4.