| Literature DB >> 23335657 |
Farhad Imani1, Purang Abolmaesumi, Mark Z Wu, Andras Lasso, Everett C Burdette, Goutam Ghoshal, Tamas Heffter, Emery Williams, Paul Neubauer, Gabor Fichtinger, Parvin Mousavi.
Abstract
This paper presents the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and nonablated tissue. For 12 ex vivo and two in situ tissue samples, RF ultrasound signals are acquired prior to, and following, high-intensity ultrasound ablation. Spatial and temporal features of these signals are used to characterize ablated and nonablated tissue in a supervised-learning framework. In cross-validation evaluation, a subset of four features extracted from RF time series produce a classification accuracy of 84.5%, an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85% for in situ data. Ultrasound RF time series is a promising approach for characterizing ablated tissue.Mesh:
Year: 2013 PMID: 23335657 DOI: 10.1109/TBME.2013.2240300
Source DB: PubMed Journal: IEEE Trans Biomed Eng ISSN: 0018-9294 Impact factor: 4.538