Have a personal or library account? Click to login
Interstitial lung diseases computer-aided imaging diagnosis, using complex networks Cover

Interstitial lung diseases computer-aided imaging diagnosis, using complex networks

Open Access
|Jun 2024

References

  1. W. D. Travis et al., “An Official American Thoracic Society/European Respiratory Society Statement: Update of the International Multidisciplinary Classification of the Idiopathic Interstitial Pneumonias,” Am. J. Respir. Crit. Care Med., vol. 188, no. 6, pp. 733–748, Sep. 2013, doi: 10.1164/rccm.201308-1483ST.
  2. K. C. Meyer, “Diagnosis and management of interstitial lung disease,” Transl. Respir. Med., vol. 2, p. 4, 2014, doi: 10.1186/2213-0802-2-4.
  3. B. Guo et al., “The interstitial lung disease spectrum under a uniform diagnostic algorithm: a retrospective study of 1,945 individuals,” J. Thorac. Dis., vol. 12, no. 7, pp. 3688–3696, Jul. 2020, doi: 10.21037/jtd-19-4021.
  4. S. Tomassetti, C. Ravaglia, and V. Poletti, “Diffuse parenchymal lung disease,” Eur. Respir. Rev., vol. 26, no. 144, p. 170004, Jun. 2017, doi: 10.1183/16000617.0004-2017.
  5. “Idiopathic Pulmonary Fibrosis (an Update) and Progressive Pulmonary Fibrosis in Adults: An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline.” Accessed: Aug. 23, 2022. [Online]. Available: https://www.atsjournals.org/doi/epdf/10.1164/rccm.202202-0399ST
  6. “Nintedanib in Progressive Fibrosing Interstitial Lung Diseases | NEJM.” Accessed: Aug. 26, 2022. [Online]. Available: https://www.nejm.org/doi/full/10.1056/NEJMoa1908681
  7. A. U. Wells, K. K. Brown, K. R. Flaherty, M. Kolb, and V. J. Thannickal, “What’s in a name? That which we call IPF, by any other name would act the same,” Eur. Respir. J., vol. 51, no. 5, May 2018, doi: 10.1183/13993003.00692-2018.
  8. “American Thoracic Society. Idiopathic pulmonary fibrosis: diagnosis and treatment. International consensus statement. American Thoracic Society (ATS), and the European Respiratory Society (ERS),” Am. J. Respir. Crit. Care Med., vol. 161, no. 2 Pt 1, pp. 646–664, Feb. 2000, doi: 10.1164/ajrccm.161.2.ats3-00.
  9. S. R. Desai, H. Prosch, and J. R. Galvin, “Plain Film and HRCT Diagnosis of Interstitial Lung Disease,” in Diseases of the Chest, Breast, Heart and Vessels 2019-2022: Diagnostic and Interventional Imaging, J. Hodler, R. A. Kubik-Huch, and G. K. von Schulthess, Eds., in IDKD Springer Series, Cham (CH): Springer, 2019. Accessed: Feb. 06, 2022. [Online]. Available: http://www.ncbi.nlm.nih.gov/books/NBK553872/
  10. T. Watadani et al., “Interobserver variability in the CT assessment of honeycombing in the lungs,” Radiology, vol. 266, no. 3, pp. 936–944, Mar. 2013, doi: 10.1148/radiol.12112516.
  11. T. Johkoh et al., “Do you really know precise radiologic-pathologic correlation of usual interstitial pneumonia?” Eur. J. Radiol., vol. 83, no. 1, pp. 20–26, Jan. 2014, doi: 10.1016/j. ejrad.2013.05.017.
  12. H. Y. Reynolds, “Diagnostic and Management Strategies for Diffuse Interstitial Lung Disease,” Chest, vol. 113, no. 1, pp. 192–202, Jan. 1998, doi: 10.1378/chest.113.1.192.
  13. R. S. Gupta, A. Koteci, A. Morgan, P. M. George, and J. K. Quint, “Incidence and prevalence of interstitial lung diseases worldwide: a systematic literature review,” BMJ Open Respir. Res., vol. 10, no. 1, p. e001291, Jun. 2023, doi: 10.1136/bmjresp-2022-001291.
  14. “Drug-induced interstitial lung disease: mechanisms and best diagnostic approaches - PMC.” Accessed: Oct. 01, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426467/
  15. “Drug-induced interstitial lung disease in the treatment of malignant l | TCRM.” Accessed: Oct. 01, 2023. [Online]. Available: https://www.dovepress.com/drug-induced-interstitial-lung-disease-in-the-treatment-of-malignant-l-peer-reviewed-fulltext-article-TCRM
  16. S. Skeoch et al., “Drug-Induced Interstitial Lung Disease: A Systematic Review,” J. Clin. Med., vol. 7, no. 10, p. 356, Oct. 2018, doi: 10.3390/jcm7100356.
  17. A. A. Trusculescu, D. Manolescu, E. Tudorache, and C. Oancea, “Deep learning in interstitial lung disease-how long until daily practice,” Eur. Radiol., vol. 30, no. 11, Art. no. 11, Nov. 2020, doi: 10.1007/s00330-020-06986-4.
  18. L. Broască et al., “A Novel Method for Lung Image Processing Using Complex Networks,” Jul. 2022, doi: 10.20944/pre-prints202207.0156.v1.
  19. A. A. Trușculescu et al., “Enhancing Imagistic Interstitial Lung Disease Diagnosis by Using Complex Networks,” Medicina (Mex.), vol. 58, no. 9, Art. no. 9, Sep. 2022, doi: 10.3390/medicina58091288.
  20. Q. Li, W. Cai, X. Wang, Y. Zhou, D. D. Feng, and M. Chen, “Medical image classification with convolutional neural network,” in 2014 13th International Conference on Control Automation Robotics Vision (ICARCV), Dec. 2014, pp. 844–848. doi: 10.1109/ICARCV.2014.7064414.
  21. L. Broască et al., “A Novel Method for Lung Image Processing Using Complex Networks,” Tomogr. Ann Arbor Mich, vol. 8, no. 4, pp. 1928–1946, Jul. 2022, doi: 10.3390/tomography8040162.
  22. “Serial CT analysis in idiopathic pulmonary fibrosis: comparison of visual features that determine patient outcome | Thorax.” Accessed: Oct. 03, 2022. [Online]. Available: https://thorax.bmj.com/content/75/8/648
  23. M. Inomata et al., “Clinical impact of the radiological indeterminate for usual interstitial pneumonia pattern on the diagnosis of idiopathic pulmonary fibrosis,” Respir. Investig., vol. 59, no. 1, pp. 81–89, Jan. 2021, doi: 10.1016/j.resinv.2020.07.001.
  24. S. L. F. Walsh et al., “Multicentre evaluation of multidiscipli-nary team meeting agreement on diagnosis in diffuse parenchymal lung disease: a case-cohort study,” Lancet Respir. Med., vol. 4, no. 7, pp. 557–565, Jul. 2016, doi: 10.1016/S2213-2600(16)30033-9.
  25. K. Simonyan and A. Zisserman, “Very Deep Convolutional Networks for Large-Scale Image Recognition,” ArXiv14091556 Cs, Apr. 2015, Accessed: Feb. 06, 2022. [Online]. Available: http://arxiv.org/abs/1409.1556
  26. G. V. L. de Lima, T. R. Castilho, P. H. Bugatti, P. T. M. Saito, and F. M. Lopes, “A Complex Network-Based Approach to the Analysis and Classification of Images,” in Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, A. Pardo and J. Kittler, Eds., Cham: Springer International Publishing, 2015, pp. 322–330. doi: 10.1007/978-3-319-25751-8_39.
  27. Y. Mourchid, M. E. Hassouni, and H. Cherifi, “A General Framework for Complex Network-Based Image Segmentation,” Multimed. Tools Appl., vol. 78, no. 14, pp. 20191–20216, Jul. 2019, doi: 10.1007/s11042-019-7304-2.
  28. L. Li et al., “Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy,” Radiology, vol. 296, no. 2, pp. E65–E71, Aug. 2020, doi: 10.1148/radiol.2020200905.
  29. M. P. Belfiore et al., “Artificial intelligence to codify lung CT in Covid-19 patients,” Radiol. Med. (Torino), vol. 125, no. 5, pp. 500–504, May 2020, doi: 10.1007/s11547-020-01195-x.
  30. R. Grassi et al., “COVID-19 pneumonia: computer-aided quantification of healthy lung parenchyma, emphysema, ground glass and consolidation on chest computed tomography (CT),” Radiol. Med. (Torino), vol. 126, no. 4, pp. 553–560, Apr. 2021, doi: 10.1007/s11547-020-01305-9.
  31. G. V. L. de Lima, T. R. Castilho, P. H. Bugatti, P. T. M. Saito, and F. M. Lopes, “A Complex Network-Based Approach to the Analysis and Classification of Images,” in Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, A. Pardo and J. Kittler, Eds., Cham: Springer International Publishing, 2015, pp. 322–330. doi: 10.1007/978-3-319-25751-8_39.
  32. G. Veloso, T. Castilho, P. Bugatti, P. Saito, and F. Lopes, A Complex Network-Based Approach to the Analysis and Classification of Images. 2015. doi: 10.1007/978-3-319-25751-8_39.
  33. Y. Mourchid, M. E. Hassouni, and H. Cherifi, “A General Framework for Complex Network-Based Image Segmentation,” Multimed. Tools Appl., vol. 78, no. 14, pp. 20191–20216, Jul. 2019, doi: 10.1007/s11042-019-7304-2.
  34. A.-L. BarabaÃsi, R. Albert, and H. Jeong, “Mean-ÿeld theory for scale-free random networks,” Phys. A, 1999.
DOI: https://doi.org/10.2478/pneum-2024-0008 | Journal eISSN: 2247-059X | Journal ISSN: 2067-2993
Language: English
Page range: 48 - 58
Published on: Jun 10, 2024
Published by: Romanian Society of Pneumology
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2024 Trușculescu Adriana, Ancușa Versavia, Broască Laura, Manolescu Diana, Pescaru Camelia, Oancea Cristian, published by Romanian Society of Pneumology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.