Segmentation of ultrasonic images by using locally adaptive filter and wavelet analysis: Detection of superficial peripheral vein by a high‐frequency ultrasonic equipment

• Atsushi Takemura

• Masayasu Ito

抄録

Ultrasonic diagnostic equipment is widely used, but has many problems such as acquiring noisy images and poorly quantifying the results for diagnosis. Therefore, a great deal of research has addressed the image processing of medical ultrasound images because of the need for automation and quantification of the diagnosis. This research began with the problem of region segmentation that automatically identifies living tissue or focus mass and currently relates to the quantification of tissue region information with the objective of tissue property diagnosis and the automatic diagnosis of 3D images. To achieve this, an accurate contour extraction method must be established. In this research, to achieve accurate region segmentation without losing the contour information in the medical ultrasound diagnostic images, we propose a new method based on an adaptive smoothing filter for suppressing speckle patterns and the 2D Gabor wavelet transform. Then we tried to automatically detect a superficial peripheral vein from an image of the forearm obtained by high‐frequency ultrasonic diagnostic equipment, which is a difficult problem for conventional image analysis techniques. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 86(1): 36–45, 2003; Published online in Wiley InterScience (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://www.interscience.wiley.com">www.interscience.wiley.com ). DOI 10.1002/ecjc.10026

収録刊行物

• Electronics and Communications in Japan (Part III: Fundamental Electronic Science)

  Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 86 (1), 36-45, 2002-09-17

  Wiley

キーワード

• Electrical and Electronic Engineering

詳細情報

• CRID: 1361978698484557312
• NII論文ID: 30006963462
• NII論文ID: 210000167931
• DOI: 10.1002/ecjc.10026
• ISSN: 15206440
• ISSN: 10420967
• Web Site: https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecjc.10026
• Web Site: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecjc.10026
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