AI-BASED IMAGE PROCESSING FORCOVID- 19DETECTIONINCHESTCTSCANIMAGES

Abstract

Big data analysts and artificial intelligence experts are paying
attention to the COVID-19 outbreak. The classification of
computed tomography (CT) chest pictures as normal or
diseased necessitates a large amount of data and an unique AI
module design. By studying CT chest scan pictures, we present
a platform that encompasses various layers of analysis and
classification of normal and pathological characteristics of
COVID-19. Specifically, the platform augments the training
dataset with a reliable collection of photos,
segmenting/detecting suspicious portions in the images, and
evaluating these regions in order to return the correct
classification. We also integrate AI algorithms after selecting
the most appropriate module for our research. Finally, we
compare the efficacy of our design to other strategies published
in the literature. The collected findings indicate that the
suggested design is 95% accurate.
COVID-19, corona score, medical imaging analysis, AI medical
platform, deep learning, computed tomography, segmentation