Phase congruency-based filtering approach combined with a convolutional network for lung CT image analysis

References

• Hemasian H, Ansari B. First case of Covid-19 presented with cerebral venous thrombosis: a rare and dreaded case. Rev Neurol (Paris). 2020;176(6):521–523.
   PubMed Web of Science ®Google Scholar
• Jajodia A, Ebner L, Heidinger B, et al. Imaging in corona virus disease 2019 (COVID-19)—a scoping review. Eur J Radiol Open. 2020;7:100237. ISSN 2352-0477.
   PubMed Web of Science ®Google Scholar
• Harapan H, Itoh N, Yufika A, et al. Coronavirus disease 2019 (COVID-19): a literature review. J Infect Public Health. 2020;13(5):667–673. ISSN 1876- 0341.
   PubMed Web of Science ®Google Scholar
• Ostad SP, Haseli S, Iranpour P. CT manifestation of COVID-19 pneumonia; role of multiplanar imaging. Acad Radiol. 2020;27(5):753–754. ISSN 1076-6332.
   PubMed Web of Science ®Google Scholar
• Kogilavani SV, et al. COVID-19 detection based on lung Ct scan using deep learning techniques. Comput Mat Method Med. 2022;2022:n. pag.
   PubMed Web of Science ®Google Scholar
• Sukanya Doddavarapu VN, Kande GB, Prabhakara Rao B. Differential diagnosis of interstitial lung diseases using deep learning networks. Imaging Sci J. 2020;68(3):170–117.
   Web of Science ®Google Scholar
• Kalisz K, Rassouli N, Dhanantwari A, et al. Noise characteristics of virtual monoenergetic images from a novel detector-based spectral CT scanner. Eur J Radiol. 2018;98:118–125. ISSN 0720-048X.
   PubMed Web of Science ®Google Scholar
• Diwakar M, Kumar M. A review on CT image noise and its denoising. Biomed Signal Process Control. 2018;42:73–88. ISSN 1746-8094.
   Web of Science ®Google Scholar
• Gavaskar RG, Chaudhury KN. Fast adaptive bilateral filtering. IEEE Trans Image Process. 2019;28:779–790.
   PubMed Web of Science ®Google Scholar
• He K, Sun J, Tang X. Guided image filtering. IEEE Trans Pattern Anal Mach Intell. 2013;35(6):1397–1409. DOI:10.1109/TPAMI.2012.213
   PubMed Web of Science ®Google Scholar
• Treece G. The bitonic filter: linear filtering in an edge-preserving morphological framework. IEEE Trans Image Process. 2016;25(11):5199–5211. DOI:10.1109/TIP.2016.2605302
   PubMed Web of Science ®Google Scholar
• Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell. 1990;12(7):629–639.
   Web of Science ®Google Scholar
• Bai J, Feng X. Image denoising using generalized anisotropic diffusion. J Math Imaging Vis. 2018;60:994–1007.
   Web of Science ®Google Scholar
• Álvarez L, Santana-Jorge F, Deriche R. Recursivity and PDEs in image processing. Proceedings 15th International Conference on Pattern Recognition. ICPR-2000. Vol. 1; 2000. p. 242–248.
   Google Scholar
• Nadernejad E, Sharifzadeh S, Korhonen J. Improving performance of wavelet-based image de-noising algorithm using complex diffusion process. Imaging Sci J. 2012;60(4):208–218.
   Web of Science ®Google Scholar
• Xu J, Jia Y, Shi Z, et al. An improved anisotropic diffusion filter with semi-adaptive threshold for edge preservation. Signal Processing. 2016;119:80–91.
   Web of Science ®Google Scholar
• Srivastava S, et al. A complex diffusion based modified fuzzy C-means approach for segmentation of ultrasound image in presence of speckle noise for breast cancer detection. Rev d'Intelligence Artif. 2020;34:419–427.
   Google Scholar
• Chao SM, Tsai DM. An anisotropic diffusion-based defect detection for low-contrast glass substrates. Image Vis Comput. 2008;26(2):187–200.
   Web of Science ®Google Scholar
• Tsai D-M, Tsai H-Y. Low-contrast surface inspection of mura defects in liquid crystal displays using optical flow-based motion analysis. Mach Vis Appl. 2011;22(4):629–649.
   Web of Science ®Google Scholar
• Chao S-M, Tsai D-M. Anisotropic diffusion with generalized diffusion coefficient function for defect detection in low-contrast surface images. Pattern Recogn. 2010;43(5):1917–1931.
   Web of Science ®Google Scholar
• Chen C, Weng C, Tseng C. An efficient detection algorithm based on anisotropic diffusion for low-contrast defect. Int J Adv Manuf Technol. 2018;94:4427–4449.
   Web of Science ®Google Scholar
• Kovesi P. Phase congruency: a low-level image invariant. Psychol Res. 2000;64:136–148.
   PubMed Web of Science ®Google Scholar
• Sudhakar MS. Fuzzy-linked phase congruency-based feature descriptors for image retrieval. Imaging Sci J. 2017;65(1):14–29.
   Web of Science ®Google Scholar
• Zhu L, Wang W, Qin J, et al. Fast feature-preserving speckle reduction for ultrasound images via phase congruency. Signal Processing. 2017;134:275–284. ISSN 165-1684.
   Web of Science ®Google Scholar
• Ronneberger O, et al. U-Net: convolutional networks for biomedical image segmentation. ArXiv abs/1505.04597; 2015.
   Google Scholar
• Milletari F, et al. V-Net: fully convolutional neural networks for volumetric medical image segmentation. 2016 Fourth International Conference on 3D Vision (3DV); 2016. p. 565–571.
   Google Scholar
• Available from: https://radiopaedia.org
   Google Scholar
• Available from: https://medicalsegmentation.com/covid19/
   Google Scholar