Optimization Ground Glass Opacities (GGO) Detection Using Multipixel
Interpolation Techniques

Optimization Ground Glass Opacities (GGO) Detection Using Multipixel
Interpolation Techniques

Computerized Tomography (CT scan), Magnetic Resonance Imaging (MRI), Multipixel Interpolation Technique,
Ground Glass Opacities (GGO), Covid-19

Ground Glass Opacities (GGO) are a picture of abnormal lung conditions characterized by white or gray areas. This picture
of GGO in the lungs could previously be detected based on the results of medical examinations such as Computerized
Tomography (CT scan) and Magnetic Resonance Imaging (MRI) images of patients suffering from Covid-19. However, from
the results of the examination, it can be seen that the CT scan and MRI images still have a noise level that is too high, causing
difficulties in describing the distribution pattern of the GGO itself. The purpose of this study was to optimize the detection of
GGO on MRI images using the Multipixel Interpolation technique. The detection process adopts several stages including image
preprocessing, edge detection process, and gradient morphological segmentation. Image preprocessing is done to remove
noise and improve the MRI input image. The edge detection process is carried out to detect lung organs automatically using
the Canny method which is optimized with the multipixel interpolation technique. The final stage of the research is the
segmentation process using a gradient morphology technique to see the spread of GGO in patients with Covid-19 contained in
the MRI image. The results of this study present an overview of the GGO pattern with fairly good results. The results of the
GGO pattern description will also measure the level of spread to see the severity of pneumonia. Based on the results presented,
this research is useful as an alternative solution in the process of diagnosis and treatment of Covid-19 patients.

Musli Yanto1
, Yogi Wiyandra2

Universitas Putra Indonesia YPTK Padang

31-10-2022

Fajar bagus W

pDF

Indonesia

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