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Title: :  Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review
PaperId: :  16907
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-16907
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Mrs.Komal KatoreAmrutvahini College of Engineering,Sangmaner
Prof.Sachin ThanekarAmrutvahini College of Engineering,Sangmaner

Abstract

Computer Engineering
CT, deep learning, COVID-19, noisy label, seg-mentation, pneumonia, medical image annotation.
The coronavirus disease pandemic of 2019 (COVID- 19) is sweeping the globe. Medical imaging, such as X-ray and computed tomography (CT), is critical in the global fight against COVID-19, and newly developed artificial intelligence (AI) technologies are enhancing the power of imaging tools and assisting medical specialists. We examine the rapid responses to COVID-19 in the medical imaging community (enabled by AI).Although deep learning algorithms have shown promise in a number of areas, they continue to struggle with noisy-labeled images throughout the training phase. Given that the quality of annotation is inextricably linked to a high level of knowledge, the issue is even more pressing in the medical picture arena. It’s still a big difficulty to get rid of the noise from noisy labels for segmentation tasks without adding more annotations.As a noninvasive imaging technique, computed tomography (CT) can detect certain lung symptoms linked with COVID-19. As a result, CT could be a useful tool for early detection and diagnosis of COVID-19. Despite its benefits, CT may have some imaging characteristics in common with COVID-19 and other kinds of pneumonia, making differentiation challenging. Due to its high power of feature extraction, artificial intelligence (AI) leveraging deep learning technology has recently proven remarkable success in the medical imaging arena. Deep learning was used to detect and distinguish between bacterial and viral pneumonia in paediatric chest radiographs.For the segmentation challenge, we present a novel noise-resistant architecture for learning from noisy labels. To better deal with lesions of varied scales and appearances, we present a unique COVID-19 Pneumonia Lesion segmentation network (COPLE-Net), which is a generalisation of Dice loss for segmentation and Mean Absolute Error (MAE) loss for robustness against noise. The noise-resistant Dice loss and COPLENet are combined with an adaptive self-ensembling architecture for training, in which a student model’s Exponential Moving Average (EMA) is employed as a teacher model that is adaptively updated by suppressing the contribution.In the context of learning from noisy labels for COVID-19 pneumonia lesion segmentation, our system with adaptive self-ensembling outperforms a regular training method and outperforms existing noise-robust training approaches.

Citations

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IJARIIE Mrs.Komal Katore, and Prof.Sachin Thanekar. "Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 2013-2019
MLA Mrs.Komal Katore, and Prof.Sachin Thanekar. "Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 2013-2019.
APA Mrs.Komal Katore, & Prof.Sachin Thanekar. (2022). Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 2013-2019.
Chicago Mrs.Komal Katore, and Prof.Sachin Thanekar. "Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 2013-2019.
Oxford Mrs.Komal Katore, and Prof.Sachin Thanekar. 'Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 2013-2019. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Automatic_Segmentation_of_COVID_19_Pneumonia_Abrasion_from_CT_Images_using_Deep_Learning__A_Review_ijariie16907.pdf (Accessed : 18 July 2022).
Harvard Mrs.Komal Katore, and Prof.Sachin Thanekar. (2022) 'Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 2013-2019IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Automatic_Segmentation_of_COVID_19_Pneumonia_Abrasion_from_CT_Images_using_Deep_Learning__A_Review_ijariie16907.pdf (Accessed : 18 July 2022)
IEEE Mrs.Komal Katore, and Prof.Sachin Thanekar, "Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 2013-2019, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/Automatic_Segmentation_of_COVID_19_Pneumonia_Abrasion_from_CT_Images_using_Deep_Learning__A_Review_ijariie16907.pdf [Accessed : 18 July 2022].
Turabian Mrs.Komal Katore, and Prof.Sachin Thanekar. "Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 (18 July 2022).
Vancouver Mrs.Komal Katore, and Prof.Sachin Thanekar. Automatic Segmentation of COVID-19 Pneumonia Abrasion from CT Images using Deep Learning: A Review. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : 18 July 2022]; 8(3) : 2013-2019. Available from: https://ijariie.com/AdminUploadPdf/Automatic_Segmentation_of_COVID_19_Pneumonia_Abrasion_from_CT_Images_using_Deep_Learning__A_Review_ijariie16907.pdf
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