Comparison of conventional edge detection methods performance in lung segmentation of COVID19 patients

Author:

Supriyanti Retno,Wibowo Farid FR,Ramadhani Yogi,Widodo Haris B

Publisher

AIP Publishing

Reference18 articles.

1. R. C. Gonzales and R. E. Woods, Digital Image Processing, 3rd editio. New Jersey: Prentice Hall, 2008.

2. Harvard Medical School, “COVID-19 basics,” Harvard Health Pusblishing, 2021. [Online]. Available: https://www.health.harvard.edu/diseases-and-conditions/covid-19-basics. [Accessed: 17-May-2021].

3. Automatic Lung Segmentation Based on Texture and Deep Features of HRCT Images with Interstitial Lung Disease

4. S. Yang, H. W. Kim, and J. Lee, “The Automated Lung Segmentation and Tumor Extraction Algorithm for PET / CT Images,” Sensors & Transducers, vol. 230, no. 2, pp. 14–20, 2019.

5. Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer

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