Automatic segmentation of pathological tissues in cardiac MRI

Elagouni, Khaoula; Ciofolo-Veit, Cybèle; Mory, Benoît

doi:10.1109/isbi.2010.5490306

Cited by 27 publications

(20 citation statements)

References 9 publications

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“…LGE CMR has high diagnostic utility and is well established in clinical practice. Interpretation of LGE CMR by physicians has been facilitated by the development of computerized intensity thresholding techniques based on the standard deviation (SD) of healthy myocardial signal intensity [12-16]. However limited studies have been focused on automatic oedema quantification.…”

Section: Introductionmentioning

confidence: 99%

Highly automatic quantification of myocardial oedema in patients with acute myocardial infarction using bright blood T2-weighted CMR

Gao

Kadir

Payne

et al. 2013

Journal of Cardiovascular Magnetic Resonance

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BackgroundT2-weighted cardiovascular magnetic resonance (CMR) is clinically-useful for imaging the ischemic area-at-risk and amount of salvageable myocardium in patients with acute myocardial infarction (MI). However, to date, quantification of oedema is user-defined and potentially subjective.MethodsWe describe a highly automatic framework for quantifying myocardial oedema from bright blood T2-weighted CMR in patients with acute MI. Our approach retains user input (i.e. clinical judgment) to confirm the presence of oedema on an image which is then subjected to an automatic analysis. The new method was tested on 25 consecutive acute MI patients who had a CMR within 48 hours of hospital admission. Left ventricular wall boundaries were delineated automatically by variational level set methods followed by automatic detection of myocardial oedema by fitting a Rayleigh-Gaussian mixture statistical model. These data were compared with results from manual segmentation of the left ventricular wall and oedema, the current standard approach.ResultsThe mean perpendicular distances between automatically detected left ventricular boundaries and corresponding manual delineated boundaries were in the range of 1-2 mm. Dice similarity coefficients for agreement (0=no agreement, 1=perfect agreement) between manual delineation and automatic segmentation of the left ventricular wall boundaries and oedema regions were 0.86 and 0.74, respectively.ConclusionCompared to standard manual approaches, the new highly automatic method for estimating myocardial oedema is accurate and straightforward. It has potential as a generic software tool for physicians to use in clinical practice.

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Section: Introductionmentioning

confidence: 99%

Highly automatic quantification of myocardial oedema in patients with acute myocardial infarction using bright blood T2-weighted CMR

Gao

Kadir

Payne

et al. 2013

Journal of Cardiovascular Magnetic Resonance

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“…The delineation of myocardial contours is a prerequisite to automatic localization and quantification of infarcts in LGE imagesnearly all such works (Kolipaka et al, 2005;Hennemuth et al, 2008;Elagouni et al, 2010;Tao et al, 2010;Valindria et al, 2011) in the literature assume that high quality myocardial segmentation is given, either manually or (semi-) automatically. Because manual delineation is not only time-consuming but also subject to inter-observer variability, it is highly desirable to automate the process.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional segmentation of the left ventricle in late gadolinium enhanced MR images of chronic infarction combining long- and short-axis information

Dong

Sun

Ong

et al. 2013

Medical Image Analysis

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“…Regan et al [5] proposed using level set algorithm to segment the edema area, the weakness of this method is that it requires expert to first define the edema boundary before the level set generates single continuous region. Elagouni et al [6] applied fast region competition formulation for accurate edema segmentation. However the work is applied to lateenhancement CMR image.…”

Section: Introductionmentioning

confidence: 99%

Automatic quantification and 3D visualisation of edema in cardiac MRI

Kadir

Gao

Payne

et al. 2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Viability assessment of heart muscle after a myocardial infarction is an important step for diagnosis and therapy planning. It is important to quantify the area of edema because it can differentiate between viable and death myocardial tissues. In this paper an automatic method to quantify cardiac edema is presented. The method is based on a combination of morphological operations and statistical thresholding. Using real MRI data it is demonstrated that the proposed method can delineate edema region comparable to manual segmentation with a linear correlation coefficient r=0.76 and the mean difference is around 9.95%. The quantification result is also used to generate 3D visualisation model showing normal myocardial wall and edema region, which will enhance clinician diagnosis capability with real pattern of edema distribution and quantitative description.

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Automatic segmentation of pathological tissues in cardiac MRI

Cited by 27 publications

References 9 publications

Highly automatic quantification of myocardial oedema in patients with acute myocardial infarction using bright blood T2-weighted CMR

Highly automatic quantification of myocardial oedema in patients with acute myocardial infarction using bright blood T2-weighted CMR

Three-dimensional segmentation of the left ventricle in late gadolinium enhanced MR images of chronic infarction combining long- and short-axis information

Automatic quantification and 3D visualisation of edema in cardiac MRI

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