Abstract
New methods of analysis and processing the digital images create unique possibilities and prospects in modern medicine because the results of many medical examinations are in the form of images. The paper presents research aimed at creating methods supporting the diagnostic process related to lung diseases diagnosed with X-ray images, such as tuberculosis and pneumoconiosis. Due to the specificity of X-ray images, i.e. the occurrence of distortions in the image, possible poor quality of these photographs, these studies have their solid grounds. An original method was proposed, thanks to which it is possible to obtain an X-ray image with better diagnostic properties. Such results were obtained because the resultive image was transformed using methods such as filtration, original solution for histogram alignment as well as point transformations of the image, and determination of object boundaries.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ogiela, M., Tadeusiewicz, R.: Image understanding methods in biomedical informatics and digital imaging. J. Biomed. Inf. 34(6), 377–386 (2001)
Pruszyński, B.: Radiologia diagnostyka obrazowa Rtg, TK, USG. MR i radioizotopy. Wydawnictwo Lekarskie PZWL (2001)
Bilir, M., Sipahi, S., Mert, A., Yanardag, H., Ozaras, R., Aki, H., Karayel, T.: Sarcoidosis presenting with isolated right paratracheal mass on chest X-ray. Eur. J. Intern. Med. 15(3), 198–199 (2004)
Gatey, C., Tattevin, P., Rioux, C., Ducot, B., Meyer, L., Bouvet, E.: Impact of early chest radiography and empirical antibiotherapy on delay in the diagnosis of pulmonary tuberculosis. Médecine et Maladies Infectieuses. 42(3), 110–113 (2012)
Lu, C.T., Chen, M.Y., Shen, J.H., Wang, L.L., Hsu, C.C.: Removal of salt-and-pepper noise for X-ray bio-images using pixel-variation gain factors. Comput. Electric. Eng. 71, 862–876 (2017)
Lee, M.S., Park, C.H., Kang, M.G.: Edge enhancement algorithm for low-dose X-ray fluoroscopic imaging. Comput. Methods Programs Biomed. 152, 45–52 (2017)
Zhang, X., Jia, F., Luo, S., Liu, G., Hu, Q.: A marker-based watershed method for X-ray image segmentation. Comput. Methods Programs Biomed. 113(3), 894–903 (2014)
Brown, M., Wilson, L., Doust, B., Gill, R., Sun, C.: Knowledge-based method for segmentation and analysis of lung boundaries in chest X-ray images. Comput. Med. Imaging Graph. 22(6), 463–477 (1998)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Walusiak, Ł., Lamża, A., Wróbel, Z. (2019). Computer Analysis of Chest X-Ray Images to Highlight Pathological Objects. In: Tkacz, E., Gzik, M., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. IBE 2018. Advances in Intelligent Systems and Computing, vol 925. Springer, Cham. https://doi.org/10.1007/978-3-030-15472-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-15472-1_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-15471-4
Online ISBN: 978-3-030-15472-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)