Image Processing Techniques on Radiological Images of Human Lungs Effected by COVID-19

A.M. Sirisha - Adikavi Nannaya University, Rajamahendravaram, India
P. Venkateswararao - Adikavi Nannaya University, Rajamahendravaram, India

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The wide spread of COVID-19 all over the world inspires every human to know and visualize its effect on human body. As   COVID-19 effects the human lungs here a number of radiological images of human lungs are analysed using an image processing technique called Threshold Segmentation. A significant difference is observed between healthy lung images and COVID-19 effected lung images.


COVID-19, Visualize, Lungs, Radiological images, Threshold Segmentation.

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Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al.: China Novel Coronavirus Investigating and Research Team. A novel Coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727-733

eng X, et al. CT imaging features of 2019 novel Coronavirus (2019-nCoV). Radiology 2020 Feb 4 [Epub]. https://doi. org/10.1148/radiol.2020200230

Bargoti, S.; Underwood, J.P. Image segmentation for fruit detection and yield estimation in apple orchards. J. Field Robot. 2017, 34, 1039–1060. [CrossRef]

Park, J.; Lee, G.; Cho, W.; Toan, N.; Kim, S.; Park, S. Moving object detection based on Clausius entropy. In Proceedings of the IEEE 10th International Conference on Computer and Information Technology (CIT), Bradford, West Yorkshire, UK, 29 June–1 July 2010; pp. 517–521.

Y.B. Chen, Oscal T.-C. Chen. (2002). Semi-automatic image segmentation using dynamic direction prediction. IEEE ICASSP. Vol 4. pp. 3369–3372.


Karsch, Q. He, Y. Duan, A fast. (2009). semiautomatic brain structure segmentation algorithm for magnetic resonance imaging. IEEE BIBM. pp. 297–302.

Chandra S,Bhat R,Singh H.(2009). A PSO based method for detection for brain tumors from MRI. In proceding of word congress on nature and biologically insipred computing. VOL 1. pp. 666-671.

Y.B. Chen, O.T.-C. Chen. (2009). Image segmentation method using thresholds automatically determined from picture contents. Article ID 140492.

Hannan, M.; Burks, T.; Bulanon, D. A real-time machine vision algorithm for robotic citrus harvesting. In Proceedings of the2007ASAEAnnual Meeting,American Society of Agricultural and Biological Engineers, Minneapolis, MN, USA, 17–20 June 2007

Elie Zemmour, Polina Kurtser and Yale Edan Automatic Parameter Tuning for Adaptive Thresholding in Fruit Detection Sensors(ISSN 1424-8220; CODEN: SENSC9) International peer-reviewed open access journal on the science and technology of sensors.

Gunatilaka,A.H.;Baertlein,B.A.Feature level and decision level fusion of noncoincidently sampled sensors for land mine detection. IEEE Trans. Pattern Anal. Mach. Intell. 2001, 23, 577–589. [CrossRef]

Kanungo, P.; Nanda, P.K.; Ghosh, A. Parallel genetic algorithm based adaptive thresholding for image segmentation under uneven lighting conditions. In Proceedings of the IEEE International Conference on Systems Man and Cybernetics (SMC), Istanbul, Turkey, 10–13 October 2010; pp. 1904–1911.

Segmentation of Lungs from Chest X-ray using Euler Number-based Thresholding, Morphological Operators and Greedy Snakes b Ebenezer Jangam, A. Chandrasekhar Rao, Uppalapati Srilakshmi, D. Yakobu y International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-7, Issue-5S4, February 2019

An Improved OTSU Algorithm Using Histogram Accumulation Moment for Ore Segmentation by Yantong Zhang and Guoying Zhang in Symmetry 2019 an open access article distributed under the creative commons attribution Licensed

A Framework with OTSU’S Thresholding Method for Fruits and Vegetables Image Segmentation International journal of Computer Applications 179(52):25-32 June 2018 .

Otsu, N. A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. 1979, 9, 62–66. [CrossRef]

Fan, H.; Xie, F.; Li, Y.; Jiang, Z.; Liu, J. Automatic segmentation of dermo’s copy images using saliency combined with Otsu threshold. Compute. Biol. Med. 2017, 85, 75–85. [CrossRef]

Goh, T.Y.; Basah, S.N.; Yazid, H.; Safar, M.J.A.; Saad, F.S.A. Performance analysis of image thresholding: Otsu technique. Measurement 2018, 114, 298–307. [CrossRef]

Kalantar, A.; Dashuta, A.; Edan, Y.; Gur, A.; Klapp, I. Estimating Melon Yield for Breeding Processes by Machine-Vision Processing of UAV Images. In Proceedings of the Precision Agriculture Conference, Montpellier, France, 8–11 July 2019.

Gajalakshmi, K.; Palanivel, S.; Nalini, N.J.; Saravanan, S.; Raghukandan, K. Grain size measurement in optical microstructure usingsupport vector regression. Optik 2017, 138, 320–327.

Segmentation Techniques For Image Analysis IJAERS/Vol. I/ Issue II/January-March,2012

Shrija Madhu, T.M.Sirisha Detection of Brain Tumor using Morphological Operatons Vol.3(2013) ISSN 2231-1009 International Journal of Research in Computer Application & Management issue-9

Manraj, Amitpal Singh Current Image Segmentation Techniques-A Review Manraj et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (2) , 2015, 1940-1942 1940 ISSN:0975-9646

Stein, M.; Bargoti, S.; Underwood, J. Image based mango fruit Detection, localization and yield estimation using multiple view geometry. Sensors 2016, 16, 1915. [CrossRef] [PubMed]

Dorj, U.O.; Lee, M.; Yun, S.S. An yield estimation in citrus orchards via fruit detection and counting using image processing. Comput. Electron. Agric. 2017, 140, 103–112.

Yogamangalam, B.Karthikeyan, “Segmentation Techniques

Comparison in Image Processing”, International Journal of

Engineering and Technology (IJET), Oct 2013.

Kavita, Ritika Saroha, Rajani Bala, Sunita Siwach, “Review paper on Overview of Image Processing and Image Segmentation”, International Journal Of Research In Computer Applications And Robotics, Vol.1 Issue.7, Pg: 113 October 2013.

Pallavi Shetty1, Deepika2, Lincy3 Review On Recent Image

Segmentation Techniques International Journal Of Current Engineering And Scientific Research (Ijcesr) Issn (Print): 2393-8374, (Online): 2394-0697, Volume-4, Issue-6, 2017


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