Open AccessExploring correlation information for image compression of four-dimensional computed tomography
Author(s) -
Hui Yan,
Ye-Xiong Li,
Jianrong Dai
Publication year - 2019
Publication title -
quantitative imaging in medicine and surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 21
eISSN - 2223-4292
pISSN - 2223-4306
DOI - 10.21037/qims.2019.06.19
Subject(s) - encoder , lossy compression , computer science , lossless compression , data compression , artificial intelligence , compression (physics) , image compression , algorithm , video compression picture types , computer vision , block matching algorithm , coding (social sciences) , inter frame , frame (networking) , reference frame , video tracking , image (mathematics) , mathematics , image processing , statistics , video processing , materials science , composite material , operating system , telecommunications
Nowadays four-dimensional computed tomography (4DCT) is popularly used in evaluating respiration-related organ motion for patients under radiotherapy. As consisting of multiple subsets of CT images, a larger storage space is needed for 4DCT. In this study, the correlations information within these subsets was explored and the popular video encoders were used for 4DCT image compression.