Name
Abstract | ||
|---|---|---|
High Intensity Focused Ultrasound (HIFU) is one of promising non-invasive thermal ablation techniques of tumor. In this paper, we present a segmentation method based on Support Vector Machine (SVM) for HIFU image-guided system where SVM is used to construct the prior model about the intensity and the shape of the structure from the training set of images and the boundaries. When segmenting a novel image, we improved level set method by incorporating this prior model. Segmentation results are demonstrated on ultrasonic images. It shows that the prior model makes segmentation process more robust and faster. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72395-0_118 | ISNN (3) |
Keywords | Field | DocType |
segmentation method,non-invasive thermal ablation technique,hifu image-guided system,support vector machine,novel image,level set method,high intensity focused ultrasound,segmentation result,segmentation process,new segmentation method,prior model | High-intensity focused ultrasound,Ultrasonic sensor,Scale-space segmentation,Computer science,Image segmentation,Artificial intelligence,Training set,Computer vision,Pattern recognition,Level set method,Segmentation,Support vector machine,Machine learning | Conference |
Volume | ISSN | Citations |
4493 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhao Zhang | 1 | 3 | 0.75 |
| Su Zhang | 2 | 60 | 9.39 |
| Wei Yang | 3 | 10 | 2.66 |
| Yazhu Chen | 4 | 96 | 13.10 |
| Hongtao Lu | 5 | 735 | 93.14 |