A New Segmentation Method Based on SVM for HIFU Image-Guided System

  • Authors:

  • Zhao Zhang;Su Zhang;Wei Yang;Ya Zhu Chen;Hong Tao Lu

  • Affiliations:

  • Biomedical Instrument Institute, Shanghai Jiao Tong University, Shanghai 200030, China;Biomedical Instrument Institute, Shanghai Jiao Tong University, Shanghai 200030, China;Biomedical Instrument Institute, Shanghai Jiao Tong University, Shanghai 200030, China;Biomedical Instrument Institute, Shanghai Jiao Tong University, Shanghai 200030, China;Dept. of Computer Science, Shanghai Jiao Tong University, Shanghai 200030, China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
  • Year:
  • 2007

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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.