Accurate detection of coronary arteries with the continuous wavelet transform

A. Munteanu; J. Cornelis; P. De Muynck; A. Bezerianos; P. Cristea

Accurate detection of coronary arteries with the continuous wavelet transform

A. Munteanu, J. Cornelis, P. De Muynck, A. Bezerianos, P. Cristea

School of Medicine

Research output: Contribution to journal › Conference article › peer-review

Abstract

We propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's performance parameters are derived for Mallat's wavelet based edge detection operator. We take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. We compare the computer determined diameters to the actual diameters; the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.

Original language	English (US)
Pages (from-to)	601-604
Number of pages	4
Journal	Computers in cardiology
State	Published - Dec 1 1997
Event	Proceedings of the 1997 24th Annual Meeting on Computers in Cardiology - Lund, Sweden Duration: Sep 7 1997 → Sep 10 1997

ASJC Scopus subject areas

Computer Science Applications
Cardiology and Cardiovascular Medicine

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title = "Accurate detection of coronary arteries with the continuous wavelet transform",

abstract = "We propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's performance parameters are derived for Mallat's wavelet based edge detection operator. We take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. We compare the computer determined diameters to the actual diameters; the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.",

author = "A. Munteanu and J. Cornelis and {De Muynck}, P. and A. Bezerianos and P. Cristea",

year = "1997",

month = dec,

day = "1",

language = "English (US)",

pages = "601--604",

journal = "Computing in Cardiology",

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note = "Proceedings of the 1997 24th Annual Meeting on Computers in Cardiology ; Conference date: 07-09-1997 Through 10-09-1997",

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T1 - Accurate detection of coronary arteries with the continuous wavelet transform

AU - Munteanu, A.

AU - Cornelis, J.

AU - De Muynck, P.

AU - Bezerianos, A.

AU - Cristea, P.

PY - 1997/12/1

Y1 - 1997/12/1

N2 - We propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's performance parameters are derived for Mallat's wavelet based edge detection operator. We take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. We compare the computer determined diameters to the actual diameters; the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.

AB - We propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's performance parameters are derived for Mallat's wavelet based edge detection operator. We take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. We compare the computer determined diameters to the actual diameters; the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.

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AN - SCOPUS:0031337293

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JO - Computing in Cardiology

JF - Computing in Cardiology

SN - 2325-8861

T2 - Proceedings of the 1997 24th Annual Meeting on Computers in Cardiology

Y2 - 7 September 1997 through 10 September 1997

ER -