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Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images

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Abstract

The carotid intima-media thickness (IMT) is the most used marker for the progression of atherosclerosis and onset of cardiovascular diseases. Computer-aided measurements improve accuracy and precision, but usually require user interaction. In this paper we characterized a new and completely automated technique for carotid segmentation and IMT measurement based on the merits of two previously developed techniques. We used an integrated approach of intelligent image feature extraction and line fitting for automatically locating the carotid artery in the image frame, followed by wall interfaces extraction based on a Gaussian edge operator. We called our system—CARES. We validated CARES on a multi-institutional database of 300 carotid ultrasound images. The IMT measurement bias was 0.032 ± 0.141 mm. Our novel approach of CARES processed 96% of the images in the database taken from two different institutions. In order to evaluate its performance, the figure-of-merit (FoM) was defined as the percent ratio between the average IMT computed by CARES and the one obtained from manual tracings by expert sonographers. The estimated FoM by CARES was 95.7%. Comparing the IMT bias of CARES with our previously published method CALEX that showed an IMT bias equal to 0.099 ± 0.137 mm, CARES improved the IMT accuracy by 67%, while increasing the standard deviation by 3%. CARES could be a useful research tool for processing large datasets in multi-center studies involving atherosclerosis.

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Abbreviations

CVD:

Cardiovascular disease

IMT:

Intima-media thickness

CA:

Carotid artery

CALEX:

Completely automated layers extraction technique

FOAM:

First-order absolute moment

CARES:

Completely automated robust edge snapper

LI:

Lumen-intima

MA:

Media-adventitia

ROI:

Region of interest

ADF :

Far (distal) adventitia layer

ADN :

Near (proximal) adventitia layer

PDM:

Polyline distance measure

GT:

Ground-truth

CALEXLI :

LI tracing by CALEX

CALEXMA :

MA tracing by CALEX

CARESLI :

LI tracing by CARES

CARESMA :

MA tracing by CARES

GTLI :

LI manual tracing (ground-truth)

GTMA :

MA manual tracing (ground-truth)

CALEXIMT :

IMT measurement by CALEX

CARESIMT :

IMT measurement by CARES

GTIMT :

IMT manual measurement (ground-truth)

\( \bar{\varepsilon }_{\text{LI}} \) :

Mean LI segmentation system error

\( \bar{\varepsilon }_{\text{MA}} \) :

Mean MA segmentation system error

\( \bar{\mu }_{\text{CALEX}} \) :

Mean CALEX IMT measurement error

\( \bar{\mu }_{\text{CARES}} \) :

Mean CARES IMT measurement error

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Acknowledgments

The authors gratefully thank Dr. Marios Pantziaris (Cyprus Institute of Neurology, Nicosia, Cyprus) and Dr. William Liboni (Neurology Dept., Gradenigo Hospital, Torino, Italy) for providing the images.

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Authors and Affiliations

  1. Biolab, Dipartimento di Elettronica, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129, Turin, Italy

    Filippo Molinari & Kristen M. Meiburger

  2. Department of ECE, Ngee Ann Polytechnic, Singapore, Singapore

    U. Rajendra Acharya

  3. MBF Bioscience, Williston, VT, USA

    Guang Zeng

  4. CTO, Global Biomedical Technologies Inc, Roseville, CA, USA

    Jasjit S. Suri

  5. Idaho State University (Aff.), Pocatello, ID, USA

    Jasjit S. Suri

Authors
  1. Filippo Molinari
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  2. U. Rajendra Acharya
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  3. Guang Zeng
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  4. Kristen M. Meiburger
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  5. Jasjit S. Suri
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Correspondence to Filippo Molinari.

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Molinari, F., Rajendra Acharya, U., Zeng, G. et al. Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images. Med Biol Eng Comput 49, 935–945 (2011). https://doi.org/10.1007/s11517-011-0781-8

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