Journal
MACHINE LEARNING IN MEDICAL IMAGING: 9TH INTERNATIONAL WORKSHOP, MLMI 2018
Volume 11046, Issue -, Pages 107-115Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-00919-9_13
Keywords
Radiomics; 3D texture; Spherical harmonics; Wavelets
Funding
- Swiss National Science Foundation [PZ00P2_154891, 205320_179069]
- Swiss National Science Foundation (SNF) [205320_179069, PZ00P2_154891] Funding Source: Swiss National Science Foundation (SNF)
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We define and investigate the Local Rotation Invariance (LRI) and Directional Sensitivity (DS) of radiomics features. Most of the classical features cannot combine the two properties, which are antagonist in simple designs. We propose texture operators based on spherical harmonic wavelets (SHW) invariants and show that they are both LRI and DS. An experimental comparison of SHW and popular radiomics operators for classifying 3D textures reveals the importance of combining the two properties for optimal pattern characterization.
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