Feature detection of tissue lesion in HIFU based on SOM.
- Author:
Hongbo CHEN
1
,
2
;
Jingtian TANG
;
Zhencheng CHEN
Author Information
1. Institute of Biomedical Engineering, School of Info-physics and Geomatics Engineering, Central South University, Changsha 410083, China. hongbochen@
2. com
- Publication Type:Journal Article
- MeSH:
High-Intensity Focused Ultrasound Ablation;
adverse effects;
instrumentation;
Humans;
Neoplasms;
therapy;
Neural Networks (Computer);
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2009;26(4):873-877
- CountryChina
- Language:Chinese
-
Abstract:
Noninvasive detection of tissue lesion is an important aided way in the process of high intensity focused ultrasound (HIFU) treatment. A new method is proposed for noninvasive detection of tissue lesion based on self-organizing maps (SOM) network. Tissue lesion, created by HIFU exposures, inevitably leads to change in B-mode image, since some new interfaces will appear in tissue. The difference-sub-image near focus of HIFU, where the tissue lesion appears, is used. Feature of lesion in difference-sub-image is extracted using the method based on SOM network. Experimental results show that the performance of the method proposed in this paper is better than that of others, such as the methods based on average gray, energy and standard deviation of difference-sub-image.
