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Model-based analysis of flow-mediated dilation and intima-media thickness.

Bartoli G, Menegaz G, Lisi M, Di Stolfo G, Dragoni S, Gori T - Int J Biomed Imaging (2009)

Bottom Line: The system allows real-time processing as well as a high level of interactivity with the user.This is obtained by a graphical user interface (GUI) enabling the cardiologist to supervise the whole process and to eventually reset the contour extraction at any point in time.Jointly with the user friendliness, low cost, and robustness, this makes the system suitable for both research and daily clinical use.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Engineering, University of Siena, 53100 Siena, Italy.

ABSTRACT
We present an end-to-end system for the automatic measurement of flow-mediated dilation (FMD) and intima-media thickness (IMT) for the assessment of the arterial function. The video sequences are acquired from a B-mode echographic scanner. A spline model (deformable template) is fitted to the data to detect the artery boundaries and track them all along the video sequence. The a priori knowledge about the image features and its content is exploited. Preprocessing is performed to improve both the visual quality of video frames for visual inspection and the performance of the segmentation algorithm without affecting the accuracy of the measurements. The system allows real-time processing as well as a high level of interactivity with the user. This is obtained by a graphical user interface (GUI) enabling the cardiologist to supervise the whole process and to eventually reset the contour extraction at any point in time. The system was validated and the accuracy, reproducibility, and repeatability of the measurements were assessed with extensive in vivo experiments. Jointly with the user friendliness, low cost, and robustness, this makes the system suitable for both research and daily clinical use.

No MeSH data available.


Related in: MedlinePlus

Results: the modeling splines correspondingto the upper and lower boundaries are represented as red curves.
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Related In: Results  -  Collection


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fig4: Results: the modeling splines correspondingto the upper and lower boundaries are represented as red curves.

Mentions: Let r be the radiusof the circular-section tube centered on the current estimation of theboundary. The radius was set to either 12 or 6 pixels in casethe downsampling option is switched off and on, respectively. Let then Ωu and Ωl be the tworegions intercepted by the tube above and below the spline curve. The averagegray values of these regions are(2)g¯ν=1/Ων/∑Ων I(i,j),where I(i, j) is the graylevel at position (i, j) in the image, /Ων/ is thecardinality of the set, and ν = u, l, where u stands for upper and v for lower, respectively. The cost function f is defined asthe difference of the average gray levels in the two regions, that is, themeasure of the contrast that we use here:(3)f=−/g¯u−g¯l/.The average intensity iscalculated columnwise such that(4)f=−∑j=1Ncol/g¯u(j)−g¯l(j)/,g¯u(j)=∑i=y^jy^j+r I(i,j),g¯l(j)=∑i=y^j−ry^j I(i,j)with being theestimation of the vertical coordinate of the spline point at horizontalposition j at the currentiteration. A multidimensional unconstrained nonlinear minimization procedure isused to determine the optimal valuesfor the y coordinates ofthe splines knots:(5)y^k,opt=miny^k{f}.Given the definition of the costfunction, it is straightforward to conclude that contrast enhancement improvesthe performance. An example of the result is shown in Figure 4, where the modelis superimposed to the ROI image. To reach the segmentation of the entire setof images, the model is propagated through the sequence such that theboundaries that have been determined in frame n serve asinitialization of the search procedure in frame n + 1. However, the GUI allows the user to supervise theprocess and eventually stop it at any time in case of unsatisfactory result. Inthis case, the spline knots can be repositioned manually for the remaining ofthe analysis. Alternatively, the user can activate a temporal filteringoperation to eliminate badly estimated contours in one or a group of frames andreplace them with an aposteriori prediction. The cardiologist can then decide about thesuitability of the result and thus decide to repeat the measurement or to dropthe corresponding set of frames.


Model-based analysis of flow-mediated dilation and intima-media thickness.

Bartoli G, Menegaz G, Lisi M, Di Stolfo G, Dragoni S, Gori T - Int J Biomed Imaging (2009)

Results: the modeling splines correspondingto the upper and lower boundaries are represented as red curves.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2665907&req=5

fig4: Results: the modeling splines correspondingto the upper and lower boundaries are represented as red curves.
Mentions: Let r be the radiusof the circular-section tube centered on the current estimation of theboundary. The radius was set to either 12 or 6 pixels in casethe downsampling option is switched off and on, respectively. Let then Ωu and Ωl be the tworegions intercepted by the tube above and below the spline curve. The averagegray values of these regions are(2)g¯ν=1/Ων/∑Ων I(i,j),where I(i, j) is the graylevel at position (i, j) in the image, /Ων/ is thecardinality of the set, and ν = u, l, where u stands for upper and v for lower, respectively. The cost function f is defined asthe difference of the average gray levels in the two regions, that is, themeasure of the contrast that we use here:(3)f=−/g¯u−g¯l/.The average intensity iscalculated columnwise such that(4)f=−∑j=1Ncol/g¯u(j)−g¯l(j)/,g¯u(j)=∑i=y^jy^j+r I(i,j),g¯l(j)=∑i=y^j−ry^j I(i,j)with being theestimation of the vertical coordinate of the spline point at horizontalposition j at the currentiteration. A multidimensional unconstrained nonlinear minimization procedure isused to determine the optimal valuesfor the y coordinates ofthe splines knots:(5)y^k,opt=miny^k{f}.Given the definition of the costfunction, it is straightforward to conclude that contrast enhancement improvesthe performance. An example of the result is shown in Figure 4, where the modelis superimposed to the ROI image. To reach the segmentation of the entire setof images, the model is propagated through the sequence such that theboundaries that have been determined in frame n serve asinitialization of the search procedure in frame n + 1. However, the GUI allows the user to supervise theprocess and eventually stop it at any time in case of unsatisfactory result. Inthis case, the spline knots can be repositioned manually for the remaining ofthe analysis. Alternatively, the user can activate a temporal filteringoperation to eliminate badly estimated contours in one or a group of frames andreplace them with an aposteriori prediction. The cardiologist can then decide about thesuitability of the result and thus decide to repeat the measurement or to dropthe corresponding set of frames.

Bottom Line: The system allows real-time processing as well as a high level of interactivity with the user.This is obtained by a graphical user interface (GUI) enabling the cardiologist to supervise the whole process and to eventually reset the contour extraction at any point in time.Jointly with the user friendliness, low cost, and robustness, this makes the system suitable for both research and daily clinical use.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Engineering, University of Siena, 53100 Siena, Italy.

ABSTRACT
We present an end-to-end system for the automatic measurement of flow-mediated dilation (FMD) and intima-media thickness (IMT) for the assessment of the arterial function. The video sequences are acquired from a B-mode echographic scanner. A spline model (deformable template) is fitted to the data to detect the artery boundaries and track them all along the video sequence. The a priori knowledge about the image features and its content is exploited. Preprocessing is performed to improve both the visual quality of video frames for visual inspection and the performance of the segmentation algorithm without affecting the accuracy of the measurements. The system allows real-time processing as well as a high level of interactivity with the user. This is obtained by a graphical user interface (GUI) enabling the cardiologist to supervise the whole process and to eventually reset the contour extraction at any point in time. The system was validated and the accuracy, reproducibility, and repeatability of the measurements were assessed with extensive in vivo experiments. Jointly with the user friendliness, low cost, and robustness, this makes the system suitable for both research and daily clinical use.

No MeSH data available.


Related in: MedlinePlus