Hai, L.Q. and Cuong, N.M. and Duc-Tan, T. (2017) Detection and classification of soft tissues using complex shear modulus estimation and decision tree algorithm. In: 10th International Conference on Advanced Technologies for Communications, ATC 2017, 18 October 2017 through 20 October 2017.
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Complex shear modulus (CSM) estimation is an effective facility to analyze the mechanical properties of tissues in terms of elasticity and viscosity. CSM can be used to detect and classify some kinds of soft tissues. However, the challenge is the estimation accuracy, and computational complexity. In this paper, we propose a 2D CSM estimation and classification of soft tissues based on the Extended Kalman Filter (EKF) and the Decision Tree (DT) algorithm. EKF is used to estimate the CSM at each spatial point by exploiting the shear wave propagation. A simple and effective decision tree algorithm is then developed for the classification of three kinds of tissues. Simulated experiment and performance study are carried out to confirm the quality of the proposed method. © 2017 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculties > Faculty of Control Engineering |
| Identification Number: | 10.1109/ATC.2017.8167619 |
| Uncontrolled Keywords: | Biomechanics; Decision trees; Elastic moduli; Elasticity; Extended Kalman filters; Histology; Kalman filters; Shear flow; Shear strain; Shear waves; Tissue; Tissue engineering; Trees (mathematics); Wave propagation; Complex shear modulus; Decision-tree algorithm; Elasticity imaging; Estimation and decisions; Performance study; Simulated experiments; Soft tissue; Spatial points; Data mining |
| Additional Information: | Conference code: 133552. Language of original document: English. |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/9664 |
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