A computational early vision model for segmentation of clinical ultrasound images

Author

Lin, Chan-Ben ; Chen, Chung-Ming ; Su, Shun-Feng

Author_Institution

Dept. of Electr. Eng., Nat. Taiwan Inst. of Technol., Taipei, Taiwan

Volume

2

fYear

1997

fDate

30 Oct-2 Nov 1997

Firstpage

605

Abstract

Image segmentation is a fundamental step for quantitative ultrasound image analysis. However, due to the intrinsic noisy nature of an ultrasound image, classic segmentation techniques are usually ineffective in performing ultrasound image segmentation. Here, the authors present a computational early vision model for segmentation of clinical ultrasound images. Their approach is based on computing perceptual similarity among local blocks of images, which has been shown to be promising by experimental results on real ultrasound images

Keywords

biomedical ultrasonics; computer vision; image segmentation; medical image processing; modelling; classic segmentation techniques; clinical ultrasound images segmentation; computational early vision model; image local blocks; intrinsic noisy nature; medical diagnostic imaging; perceptual similarity computation; quantitative ultrasound image analysis; Biomedical imaging; Computational modeling; Computer vision; Humans; Image edge detection; Image processing; Image segmentation; Laplace equations; Magnetic resonance imaging; Ultrasonic imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1094-687X

Print_ISBN

0-7803-4262-3

Type

conf

DOI

10.1109/IEMBS.1997.757683

Filename

757683