Structure-adaptive B-snake for segmenting complex objects

Y. Wang; E. K. Teoh; Dinggang Shen

Structure-adaptive B-snake for segmenting complex objects

Y. Wang, E. K. Teoh, Dinggang Shen

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, we presented a structure-adaptive B-snake model for segmenting the complex structures in medical images. A strategy of automatic control-point insertion, adaptive to the structure of the studied object, has been proposed. Furthermore, a method of minimum mean square energy (MMSE) is developed to iteratively estimate the position of those control points in the B-snake model. By applying the proposed structure-adaptive B-snake model to medical images, we show that our method is robust and accurate in object contour extraction.

Original language	English
Pages	769-772
Number of pages	4
Publication status	Published - 2001
Event	IEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece Duration: 2001 Oct 7 → 2001 Oct 10

Other

Other	IEEE International Conference on Image Processing (ICIP)
Country/Territory	Greece
City	Thessaloniki
Period	01/10/7 → 01/10/10

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Cite this

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title = "Structure-adaptive B-snake for segmenting complex objects",

abstract = "In this paper, we presented a structure-adaptive B-snake model for segmenting the complex structures in medical images. A strategy of automatic control-point insertion, adaptive to the structure of the studied object, has been proposed. Furthermore, a method of minimum mean square energy (MMSE) is developed to iteratively estimate the position of those control points in the B-snake model. By applying the proposed structure-adaptive B-snake model to medical images, we show that our method is robust and accurate in object contour extraction.",

author = "Y. Wang and Teoh, {E. K.} and Dinggang Shen",

year = "2001",

language = "English",

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TY - CONF

T1 - Structure-adaptive B-snake for segmenting complex objects

AU - Wang, Y.

AU - Teoh, E. K.

AU - Shen, Dinggang

PY - 2001

Y1 - 2001

N2 - In this paper, we presented a structure-adaptive B-snake model for segmenting the complex structures in medical images. A strategy of automatic control-point insertion, adaptive to the structure of the studied object, has been proposed. Furthermore, a method of minimum mean square energy (MMSE) is developed to iteratively estimate the position of those control points in the B-snake model. By applying the proposed structure-adaptive B-snake model to medical images, we show that our method is robust and accurate in object contour extraction.

AB - In this paper, we presented a structure-adaptive B-snake model for segmenting the complex structures in medical images. A strategy of automatic control-point insertion, adaptive to the structure of the studied object, has been proposed. Furthermore, a method of minimum mean square energy (MMSE) is developed to iteratively estimate the position of those control points in the B-snake model. By applying the proposed structure-adaptive B-snake model to medical images, we show that our method is robust and accurate in object contour extraction.

UR - http://www.scopus.com/inward/record.url?scp=0035168278&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0035168278

SP - 769

EP - 772

T2 - IEEE International Conference on Image Processing (ICIP)

Y2 - 7 October 2001 through 10 October 2001

ER -

Structure-adaptive B-snake for segmenting complex objects

Abstract

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ASJC Scopus subject areas

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