Advanced search
Publication Cover
Cogent Engineering Volume 10, 2023 - Issue 1
Submit an article Journal homepage
1,048
Views
1
CrossRef citations to date
0
Altmetric
Biomedical Engineering

Improvement of chest X-ray image segmentation accuracy based on FCA-Net

Rima Tri Wahyuningrum1 Department of Informatics Engineering, Faculty of Engineering, University of Trunojoyo Madura, Bangkalan, IndonesiaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1760-9341View further author information
ORCID Icon,
Indah Yunita1 Department of Informatics Engineering, Faculty of Engineering, University of Trunojoyo Madura, Bangkalan, IndonesiaView further author information
,
Indah Agustien Siradjuddin1 Department of Informatics Engineering, Faculty of Engineering, University of Trunojoyo Madura, Bangkalan, IndonesiaORCID Iconhttps://orcid.org/0000-0002-2854-6975View further author information
ORCID Icon,
Budi Dwi Satoto1 Department of Informatics Engineering, Faculty of Engineering, University of Trunojoyo Madura, Bangkalan, IndonesiaORCID Iconhttps://orcid.org/0000-0002-1919-0540View further author information
ORCID Icon,
Amillia Kartika Sari2 Department of Health, Faculty of Vocational Studies, Universitas Airlangga, Surabaya, IndonesiaORCID Iconhttps://orcid.org/0000-0001-9908-3974View further author information
ORCID Icon &
Anggraini Dwi Sensusiati3 Department of Radiology, Medical Faculty, Universitas Airlangga, Surabaya, IndonesiaORCID Iconhttps://orcid.org/0000-0002-9841-1769View further author information
ORCID Icon
Article: 2229571 | Received 25 May 2023, Accepted 19 Jun 2023, Published online: 25 Jun 2023

References

  • Cheng, J., Tian, S., Yu, L., Lu, H., & Lv, X. (2020). Fully convolutional attention network for biomedical image segmentation. Artificial Intelligence in Medicine, 107(July), 101899. https://doi.org/10.1016/j.artmed.2020.101899
  • Chest X-ray, 2020. RadiologyInfo. Retrieved October 1, 2022, https://www.radiologyinfo.org/en/info/chestrad
  • Degerli, A., Ahishali, M., Yamac, M., Kiranyaz, S., Chowdhury, M. E. H., Hameed, K., Hamid, T., Mazhar, R., & Gabbouj, M. (2021). COVID-19 infection map generation and detection from chest X-ray images. Health Information Science Systems, 9(1). https://doi.org/10.1007/s13755-021-00146-8
  • Gao, S. H., Cheng, M. M., Zhao, K., Zhang, X. Y., Yang, M. H., & Torr, P. (2021). Res2net: A new Multi-Scale backbone architecture. IEEE Transactions Pattern Analysis Machine Intelligent, 43(2), 652–16. https://doi.org/10.1109/TPAMI.2019.2938758
  • Hooda, R., Mittal, A., & Sofat, S. (2018). An efficient variant of Fully-Convolutional network for segmenting lung fields from chest radiographs. Wireless Personal Communications, 101(3), 1559–1579. https://doi.org/10.1007/s11277-018-5777-3
  • Kalinovsky, A. and Kovalev, V. (2017, July), Lung image segmentation using deep learning methods and convolutional neural networks. Proceedings of the International Conference on Pattern Recognition and Information, Minsk, Belarus State University (pp. 21–24).
  • Mittal, A., Hooda, R., & Sofat, S. (2018). LF-Segnet: A fully convolutional Encoder–Decoder network for segmenting lung fields from chest radiographs. Wireless Personal Communications, 101(1), 511–529. https://doi.org/10.1007/s11277-018-5702-9
  • Munawar, F., Azmat, S., Iqbal, T., Gronlund, C., & Ali, H. (2020). Segmentation of lungs in chest X-Ray image using generative adversarial networks. IEEE Access, 8, 153535–153545. https://doi.org/10.1109/ACCESS.2020.3017915
  • Rizwan I Haque, I., & Neubert, J. (2020). Deep learning approaches to biomedical image segmentation. Information Medical Unlocked, 18, 100297. https://doi.org/10.1016/j.imu.2020.100297
  • RSUA, Radiologi. (2023). RSUA chest X-Ray dataset. Mendeley Data, V1. https://doi.org/10.17632/2jg8vfdmpm.1
  • Saidy, L., & Lee, C. C. (2018, May). Chest X-ray image segmentation using encoder-decoder convolutional network. Proceedings of the 2018 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), Taichung, Taiwan (pp. 1–2). IEEE.
  • Souza, J. C., Otávio, J., Diniz, B., Ferreira, J. L., Lucca, G., Silva, A. C., & De Paiva, A. C. (2019). An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks. Computer Methods and Programs in Biomedicine, 177, 285–296. https://doi.org/10.1016/j.cmpb.2019.06.005
  • Su, R., Zhang, D., Liu, J., & Cheng, C. (2021). MSU-Net: Multi-Scale U-Net for 2D medical image segmentation. Frontiers in Genetics, 12. https://doi.org/10.3389/fgene.2021.639930
  • Tahir, A. M., Chowdhury, M. E. H., Khandakar, A., Rahman, T., Qiblawey, Y., Khurshid, U., Kiranyaz, S., Ibtehaz, N., Rahman, M. S., Al-Maadeed, S., Mahmud, S., Ezeddin, M., Hameed, K., & Hamid, T. (2021). COVID-19 infection localization and severity grading from chest X-ray images. Computers in Biology and Medicine, 139, 105002. https://doi.org/10.1016/j.compbiomed.2021.105002
  • Wang, R., Lei, T., Cui, R., Zhang, B., Meng, H., & Nandi, A. K. (2022). Medical image segmentation using deep learning: A survey. IET Image Processing, 16(5), 1243–1267. https://doi.org/10.1049/ipr2.12419
  • Wang, Q., Liu, Q., Luo, G., Liu, Z., Huang, J., Zhou, Y., Zhou, Y., Xu, W., & Cheng, J. Z. (2020). Automated segmentation and diagnosis of pneumothorax on chest X-rays with fully convolutional multi-scale ScSE-DenseNet: A retrospective study. BMC Medical Informaticae Decision Mak, 20(14), 1–13. https://doi.org/10.1186/s12911-020-01325-5

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.