Fractional Wavelet Scattering Network and Applications

Abstract : Objective - This study introduces a fractional wavelet scattering network (FrScatNet), which is a generalized translation invariant version of the classical wavelet scattering network. Methods - In our approach, the FrScatNet is constructed based on the fractional wavelet transform (FRWT). The fractional scattering coefficients are iteratively computed using FRWTs and modulus operators. The feature vectors constructed by fractional scattering coefficients are usually used for signal classification. In this paper, an application example of the FrScatNet is provided in order to assess its performance on pathological images. First, the FrScatNet extracts feature vectors from patches of the original histological images under different orders. Then we classify those patches into target (benign or malignant) and background groups. And the FrScatNet property is analyzed by comparing error rates computed from different fractional orders, respectively. Based on the above pathological image classification, a gland segmentation algorithm is proposed by combining the boundary information and the gland location. Results - The error rates for different fractional orders of FrScatNet are examined and show that the classification accuracy is improved in fractional scattering domain. We also compare the FrScatNet-based gland segmentation method with those proposed in the 2015 MICCAI Gland Segmentation Challenge and our method achieves comparable results. Conclusion - The FrScatNet is shown to achieve accurate and robust results. More stable and discriminative fractional scattering coefficients are obtained by the FrScatNet in this paper. Significance - The added fractional order parameter is able to analyze the image in the fractional scattering domain.
Complete list of metadatas

Cited literature [44 references]  Display  Hide  Download

https://hal-univ-rennes1.archives-ouvertes.fr/hal-01839322
Contributor : Lotfi Senhadji <>
Submitted on : Saturday, July 14, 2018 - 2:30:40 PM
Last modification on : Friday, July 5, 2019 - 10:16:02 AM
Long-term archiving on : Tuesday, October 16, 2018 - 1:45:14 AM

File

FINAL VERSION.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Li Liu, Jiasong Wu, Dengwang Li, Lotfi Senhadji, Huazhong Shu. Fractional Wavelet Scattering Network and Applications. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2019, 66 (2), pp.553-563. ⟨10.1109/TBME.2018.2850356⟩. ⟨hal-01839322⟩

Share

Metrics

Record views

56

Files downloads

98