Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Power-law shot noise model for the ultrasound RF echo
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Power-law shot noise and its relationship to long-memoryα-stable processes
IEEE Transactions on Signal Processing
Signal modeling with self-similar α-stable processes: thefractional Levy stable motion model
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
Ultrasound is a safe, inexpensive and widely available tissue imaging modality, but its use in breast cancer detection is rather limited. Currently there is a significant amount of research devoted to extracting objective features from the ultrasound return signal, to be used in automatic tissue characterization. In this paper we investigate the parameters of the power-law shot noise (PLSN) model that was proposed in [IEEE Trans. UFFC 48 (2001) 953] as potential tissue characterization features. The PLSN model parameters are estimated from a database of 100 clinical ultrasound images of the breast, taken from 25 patients, and receiver operating characteristic (ROC) analysis is subsequently applied to quantify their ability to differentiate between tumorous and non-tumorous tissue and also between malignant and benign tumors. The obtained results indicate a maximum ROC area of 97% for the tumorous versus nontumorous decision, while a maximum ROC area of 81% is obtained for the benign versus malignant decision. The latter result can be further improved by using the PLSN model parameters along with parameters of the K-distribution model, the combination yielding a maximum ROC area of 88.9%.