Intravascular ultrasound-based tissue characterization using modular network self-organizing map
| Autor: | Kazuhiro Tokunaga, Noriaki Suetake, Eiji Uchino, Hiroki Tanaka |
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| Rok vydání: | 2016 |
| Předmět: |
Self-organizing map
medicine.diagnostic_test business.industry Computer science Pattern recognition 02 engineering and technology Tissue characterization 030204 cardiovascular system & hematology Modular design 03 medical and health sciences 0302 clinical medicine Feature (computer vision) Coronary plaque Intravascular ultrasound 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Artificial intelligence business Software |
| Zdroj: | Applied Soft Computing. 44:89-100 |
| ISSN: | 1568-4946 |
| DOI: | 10.1016/j.asoc.2016.03.017 |
| Popis: | Graphical abstractDisplay Omitted HighlightsThis work proposes new IVUS-based tissue characterization method that uses a mnSOM.The proposed method can create a map of various dynamical features from the radio-frequency signal.The proposed method has a high generalization performance for IVUS -based tissue characterization as compared with conventional method. The intravascular ultrasound-based tissue characterization of coronary plaque is important for the early diagnosis of acute coronary syndromes. The conventional tissue characterization techniques however cannot obtain sufficient identification accuracy for various tissue properties, because the feature employed for characterization are static features, which lack dynamical information about backscattered radio-frequency (RF) signals.In this work, we propose a new intravascular ultrasound-based tissue characterization method that uses a modular network self-organizing map (mnSOM) in which each module is composed of an autoregressive model for representing the dynamics of the RF signals.The proposed method can create a map of various dynamical features from the RF signal. This map enables generalized tissue characterizations. The proposed method is verified by comparing its tissue characterization performance with that of the conventional method using real intravascular ultrasound signals. |
| Databáze: | OpenAIRE |
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