Computed Tomography Image Processing Analysis in COVID-۱۹ Patient

سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 115

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شناسه ملی سند علمی:

CSUMSMED07_279

تاریخ نمایه سازی: 20 دی 1401

چکیده مقاله:

Background and aim: COVID-۱۹ pandemic is an infectious disease that has affected millions of individuals all over the world, and it has caused thousands of deaths since December ۱۹, ۲۰۱۹. due to the similarity of the clinical symptoms of this diseases with other infectious diseases of the lungs, accurate diagnosis is very important, for this reason ,CT scan image analysis is used as diagnosis supplement along with laboratory methods. The main purpose of this review article is the use of artificial intelligent, the provision of intelligent and automated image analysis solution for accurate diagnosis of COVID ۱۹.Materials and method: In this review article the keywords were COVID ۱۹ , Computed Tomograhy and image Analysis based on PubMed, Scopus and Google scholar databases during the ۲۰۲۰-۲۰۲۱s.Results: detection of COVID ۱۹ in CT scan images is somewhat difficult and time consuming, that is why diagnosis tools based in deep learning and the use of Radiomix have been developed that can accurately diagnose the presence and severity of this diseases.recent study show that a CT scan of a patient COVID ۱۹ shows signs of GGO* ,so it is important to find unnatural areas such as GGO.one of the proposed methods in the field of artificial intelligence to identify these areas is the UNet++. this method has been able to diagnosis cases with good accuracy and sensitivity.another solution is to uses the Radiomix analysis method ,this method is also use to classify the characteristics and diagnose the COVID ۱۹.Conclusion: Identification of GGO is required for the derivation of diagnostic conclusions and the characterization of the contents in the pulmonary parenchyma area. Automated identification of the in the CT images from these COVID-۱۹ patients is a challenging issue for medical image processing. In this research, we effectively overcame the problem of locating and detecting GGO in atients with COVID ۱۹.

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نویسندگان

Maryam Elikaei Moghadam

Medical Imaging Department, School of Medicine, Iran University of Medical Sciences(IUMS), Tehran, Iran