Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.
A larger thrombus in AAA was associated with a higher AAA growth rate, but also with a lower wall stress. Therefore, weakening of the AAA wall, under the influence of thrombus, may play a more imminent role in the process of AAA growth than the stress acting on the wall.
Objective
We sought to assess the relationship of left ventricular (LV) trabeculae and papillary muscles (TPM) with clinical characteristics in a community-based, free living adult cohort and to determine the effect of TPM on quantitative measures of LV volume, mass and ejection fraction (EF).
Background
Hypertrabeculation has been associated with adverse cardiovascular events, but the distribution and clinical correlates of the volume and mass of the TPM in a normal left ventricle have not been well characterized.
Methods
Short-axis cine cardiovascular magnetic resonance (CMR) images, obtained using a steady-state free precession sequence, from 1494 members of the Framingham Offspring cohort were analyzed using software that automatically segments TPM. Absolute TPM volume, TPM as a fraction of end-diastolic volume (TPM/EDV), and TPM mass as a fraction of LV mass (TPMm/LVM) were determined on all Offspring and in a referent group of Offspring free of clinical cardiovascular disease and hypertension.
Results
In the referent group (aged 61±9 years, with 262 men and 423 women) TPM was 23±3 % of LV EDV in both sexes (p=0.9). TPM/EDV decreased with age (p<0.02) but was not associated with body mass index (BMI). TPMm/LVM was inversely correlated with age (p<0.0001), BMI (p<0.018) and systolic blood pressure (p<0.0001). Among all 1494 participants (699 men) LV volumes decreased 23%, LV mass increased 28% and EF increased by 7.5 EF units (p<0.0001) when TPM were considered myocardial mass rather than part of the LV blood pool.
Conclusions
Global CMR LV parameters are significantly affected by whether TPM are considered as part of the LV blood pool or as part of LV mass. Our cross-sectional data from a healthy referent group of adults free of clinical cardiovascular disease demonstrate that TPM/EDV decreases with increasing age in both sexes, but is not related to hypertension or obesity.
We have developed a method for automatic contour propagation in cine cardiac magnetic resonance images. The method consists of a new active contour model that tries to maintain a constant contour environment by matching gray values in profiles perpendicular to the contour. Consequently, the contours should maintain a constant position with respect to neighboring anatomical structures, such that the resulting contours reflect the preferences of the user. This is particularly important in cine cardiac magnetic resonance images because local image features do not describe the desired contours near the papillary muscle. The accuracy of the propagation result is influenced by several parameters. Because the optimal setting of these parameters is application dependent, we describe how to use full factorial experiments to optimize the parameter setting. We have applied our method to cine cardiac magnetic resonance image sequences from the long axis two-chamber view, the long axis four-chamber view, and the short axis view. We performed our optimization procedure for each contour in each view. Next, we performed an extensive clinical validation of our method on 69 short axis data sets and 38 long axis data sets. In the optimal parameter setting, our propagation method proved to be fast, robust, and accurate. The resulting cardiac contours are positioned within the interobserver ranges of manual segmentation. Consequently, the resulting contours can be used to accurately determine physiological parameters such as stroke volume and ejection fraction.
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