ABSTRACT
For many clinical goals like surgical planning and radiotherapy treatment planning is necessary to understand the anatomical structures of the organ that is targeted. At the same time the 2D/3D shape of the organ is important to be reconstructed for the benefit of the doctors. For that reason, accurate segmentation techniques must be proposed to overcome the big data medical image storage problem. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.
Subject(s)
COVID-19 , Imaging, Three-Dimensional , COVID-19/diagnostic imaging , Humans , Image Processing, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Tomography, X-Ray Computed/methodsABSTRACT
During the last months the Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat. Transmission of the infection has rapidly increased in Europe as well as in Greece, living behind a huge number of deaths. During this situation an analysis of the spread of the disease must be undertaken and characteristics of the virus must be recognized. For the analysis of the impact of the disease in the population during this time period, epidemiological indexes have been introduced.