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Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images

Authors :
Che, Fengying
Shi, Ruichuan
Wu, Jian
Li, Haoran
Li, Shuqin
Chen, Weixing
Zhang, Hao
Li, Zhi
Cui, Xiaoyu
Che, Fengying
Shi, Ruichuan
Wu, Jian
Li, Haoran
Li, Shuqin
Chen, Weixing
Zhang, Hao
Li, Zhi
Cui, Xiaoyu
Publication Year :
2020

Abstract

The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process that cannot be fully reflected by only static characteristics. This study proposes a new dynamic radiomics feature extraction workflow that uses time-dependent tomographic images of the same patient, focuses on the changes in image features over time, and then quantifies them as new dynamic features for diagnostic or prognostic evaluation. We first define the mathematical paradigm of dynamic radiomics and introduce three specific methods that can describe the transformation process of features over time. Three different clinical problems are used to validate the performance of the proposed dynamic feature with conventional 2D and 3D static features.<br />Comment: Appl Intell (2022)

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1228443034
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1007.s10489-021-03053-3