[Effects of different wavelet filters on correlation and diagnostic performance of radiomics features].
Zhong Nan Da Xue Xue Bao Yi Xue Ban
; 44(3): 244-250, 2019 Mar 28.
Article
em Zh
| MEDLINE
| ID: mdl-30971515
ABSTRACT
OBJECTIVE:
To investigate the effects of different wavelet filters on correlation and diagnostic performance of radiomics features.â©Methods:
A total of 143 colorectal cancer (CRC) patients (64 positive in lymph node metastasis and 79 negative) with contrast-enhanced CT examination were recruited. After labeling the tumor area by experienced radiologists, radiomics wavelets features based on 48 different wavelets were extracted using in-house software coded by Matlab. The correlation coefficients of the features with same names between different wavelets were calculated and got the distribution of high-correlation features between each wavelet. The least absolute shrinkage and selection operator (LASSO) was used to build signatures between lymph node metastasis and wavelet features data set based on different wavelets. The numbers of features in signatures and diagnostic performance were compared using Delong's test.â©Results:
With the difference of wavelet order increased, the number of high-correlation features between two wavelets decreased. Some features were prone to high correlation between different wavelets. When building radiomics signature based on single wavelet, signatures built from 'rbio2.2', 'sym7' and 'db7' did well in predicting lymph node metastasis. The signature based on Daubechies wavelet feature set had the highest performance in predicting lymph node metastasis, while the signature from Biorthogonal wavelet features was worst. Improvement was significant in diagnostic performance after excluding the high-correlation features in the whole features set (P=0.004).â©Conclusion:
In order to reduce the data redundancy of features, it is recommended to select wavelets with large differences in wavelet orders when calculating radiomics wavelet features. It is necessary to remove high correlation features for improving the diagnostic performance of radiomics signature.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Colorretais
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
Zh
Revista:
Zhong Nan Da Xue Xue Bao Yi Xue Ban
Assunto da revista:
MEDICINA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
China