Performance evaluation of the section of 3D reconstruction based on different PET/CT image fusion sequence
Autor: | Wen-Lin Huang, Yu-Lin Hsiao, Rong-Chin Lo |
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Rok vydání: | 2015 |
Předmět: |
Computer science
Wavelet Analysis Biomedical Engineering Biophysics Health Informatics Bioengineering Standard deviation Biomaterials Imaging Three-Dimensional Wavelet medicine Humans Entropy (information theory) Computer vision Spatial analysis PET-CT Image fusion medicine.diagnostic_test business.industry 3D reconstruction Positron emission tomography Positron-Emission Tomography Artificial intelligence Tomography X-Ray Computed business Algorithms Information Systems |
Zdroj: | Technology and Health Care. 24:S357-S367 |
ISSN: | 1878-7401 0928-7329 |
DOI: | 10.3233/thc-151093 |
Popis: | In recent years, positron emission tomography imaging (PET) and Computed tomography (CT) fusion images can be observed metabolic information, they can get a more accurate spatial information. People have to construct 3D models in the first place when they try to examine images from different angles. Once a cross-section which we want to inspect has been revealed, it can be observed from any angles. However, a issue people encounter in above-mentioned procedures is that they have to either process images fusion at the beginning and then reconstruct the 3D models with these images to generate section or rebuilt the 3D models with these images and fuse section images as the second step. The main objective of this research is to discriminate the divergences and merits between two types of procedures.This research discovers that two different procedures will exactly bring about dissimilar types of images. Therefore, this research particularly aims at the analysis of two images and evaluates the extent of fringe and remaining information. We calculates entropy and standard deviation of the images. Nevertheless, finding section on 3D models first and fusing images secondly will generate the images which retain more information. |
Databáze: | OpenAIRE |
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