Page 32 - AIH-2-1

Artificial Intelligence in Health COVID-19 diagnosis: FPA, k-NN, and SVM classifiers

Nucl Eng Technol. 2020;52(10):2313-2319. 2015;24(12):5854-5867.
doi: 10.1016/j.net.2020.03.011 doi: 10.1109/TIP.2015.2488902
18. Prabin A, Veerappan J. Automatic segmentation of lung CT 30. Ali AM, Farag AA. Automatic Lung Segmentation of
images by CC based region growing. J Theor Appl Inform Volumetric Low-dose CT Scans Using Graph Cuts. In:
Technol. 2014;68(1):63-69. International Symposium on Visual Computing; 2008.
p. 258-267.
19. Avinash S, Manjunath K, Kumar SS. An Improved Image
Processing Analysis for the Detection of Lung Cancer Using 31. Bhuvaneswari P, Therese BA. Detection of cancer in lung
Gabor Filters and Watershed Segmentation Technique. In: with k-NN classification using genetic algorithm. Procedia
IEEE International Conference on Inventive Computation Mater Sci. 2015;10:433-440.
Technologies; 2016. doi: 10.1016/j.mspro.2015.06.077
20. Kumar SL, Swathy M, Sathish S, Sivaraman J, Rajasekar M. 32. Filho DC, Silva AO, Paiva AC, Nunes RA, Gattass M. Computer-
Identification of lung cancer cell using watershed aided diagnosis system for lung nodules based on computed
segmentation on CT images. Indian J Sci Technol. 2016;9:1-4. tomography using shape analysis, a genetic algorithm, and
doi: 10.17485/ijst/2016/v9i1/85765 SVM. Med Biol Eng Comput. 2017;55:1129-1146.

21. Shojaii R, Alirezaie J, Babyn P. Automatic Lung Segmentation doi: 10.1007/s11517-016-1577-7
in CT Images Using Watershed Transform. In: IEEE 33. Herrmann P, Busana M, Cressoni M, et al. Using artificial
International Conference on Image Processing; 2005. intelligence for automatic segmentation of CT lung images
22. Nithila EE, Kumar SS. Segmentation of lung from CT in acute respiratory distress syndrome. Front Physiol.
using various active contour models. Biomed Signal Process 2021;12:76118.
Control. 2019;47:57-62. doi: 10.3389/fphys.2021.676118
23. Kasinathan G, Jayakumar S, Gandomi AH, et al. Automated 34. Shi F, Wang J, Shi J, et al. Review of artificial intelligence
3-D lung tumor detection and classification by an active techniques in imaging data acquisition, segmentation, and
contour model and CNN classifier. Expert Syst Appl. diagnosis for COVID-19. IEEE Rev Biomed Eng. 2021;14:4-15.
2019;15(134):112-119.
doi: 10.1109/RBME.2020.2987975
doi: 10.1016/j.eswa.2019.05.041
35. Van EM, Hoop D, Viergever MA, Prokop M, Ginneken
24. Sangamithraa PB, Govindaraju S. Lung Tumor Detection BV. Automatic lung segmentation from thoracic computed
and Classification Using EK-Mean Clustering. In: IEEE tomography scans using a hybrid approach with error
International Conference on Wireless Communications, Signal detection. Med Phys. 2009;36:2934-2947.
Processing and Networking (WiSPNET); 2016. p. 2201-2206.
doi: 10.1118/1.3147146
25. Joon P, Bajaj SB, Jatain A. Segmentation and detection of lung
cancer using image processing and clustering techniques. In: 36. Doi K. Computer-aided diagnosis in medical imaging:
Advanced Computing and Intelligent Engineering. Germany: Historical review, current status, and future potential.
Springer Nature; 2019. p. 13-23. Comput Med Imaging Graph. 2007;31(5):198-211.
26. Xu M, Qi S, Yue Y, et al. Segmentation of lung parenchyma in doi: 10.1016/j.compmedimag.2007.02.002
CT images using CNN trained with the clustering algorithm 37. Choi YJ, Baek JH, Park HS, et al. A computer-aided diagnosis
generated dataset. Biomed Eng Online. 2019;18:2. system using artificial intelligence for the diagnosis and
doi: 10.1186/s12938-018-0619-9 characterization of thyroid nodules on ultrasound: Initial
clinical assessment. Thyroid. 2017;27(4):546-552.
27. Farag AA, Munim HE, Graham JH, Farag AA. A novel
approach for lung nodules segmentation in chest CT using doi: 10.1089/thy.2016.0372
level sets. IEEE Trans Image Process. 2013;22:5202-5213. 38. Isaac A, Nehemiah HK, Dunston DS, Christo VRE,
doi: 10.1109/TIP.2013.2282899 Kannan A. Feature selection using competitive coevolution
of bio-inspired algorithms for the diagnosis of pulmonary
28. Swierczynski P, Papież BW, Schnabel JA, Macdonald C. emphysema. Biomed Signal Process Control. 2022;72:103340.
A level-set approach to joint image segmentation and
registration with application to CT lung imaging. Comput doi: 10.1016/j.bspc.2021.103340
Med Imaging Graph. 2018;65:58-68. 39. Khin Y, Maneerat N, Sreng S, Hamamoto K. Ensemble deep
learning for the detection of COVID-19 in unbalanced chest
doi: 10.1016/j.compmedimag.2017.06.003
X-ray dataset. Appl Sci. 2021;11(22):10528.
29. Wei J, Deihui X, Zhang B, Wang L, Kopriva I, Chen X.
Random walk and graph cut for co-segmentation of lung doi: 10.3390/app112210528
tumor on PET-CT images. IEEE Trans Image Process. 40. Venkatesan R, Kadry R, Thanaraj KP, Kamalanand K, Seo S.

Volume 2 Issue 1 (2025) 26 doi: 10.36922/aih.3349