Open AccessThreshold Determination in Multislice CT-SCan using Improved Marching Cube Algorithm (IMCA) for 3D Image Reconstruction Process (3D-IRP)
Author(s) -
I L I Purnama,
Alva Edy Tontowi,
- Herianto
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1655/1/012088
Subject(s) - dicom , marching cubes , multislice , computer science , computer vision , artificial intelligence , volume (thermodynamics) , process (computing) , software , medical imaging , multislice computed tomography , tomography , visualization , nuclear medicine , computed tomography , radiology , medicine , physics , quantum mechanics , programming language , operating system
Medical diagnostic information has been a change in clinical medicine development, including medical image and computer technology. The paper aims to determine the threshold for the 3D-IRP with a multislice Computerized Tomography Scan (CT-Scan). The 3D-IRP method is the IMCA technique. Skull and Sternum are the focus of the 3D medical image. It is in the multislice CT-Scan format of Digital Imaging and Communications in Medicine (DICOM). Surface volume and area, and visual shape are performance criteria of the 3D-IRP are matching with a software package (InVesalius ver. 3.1). The optimum threshold for the 3D bone representation of objects is 210. The difference in 3D image surface area and volume between the prototype's performance and the software package is smaller than 0.50%. Based on the three radiologists, the Skull and Sternum's visual shape is roughly 100% balanced.