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44 results on '"Mollet, N."'

24. Prevalence and characteristics of coronary artery disease in a population with suspected ischaemic heart disease using CT coronary angiography: correlations with cardiovascular risk factors and clinical presentation

Author

Cademartiri, F., Romano, M., Seitun, S., Maffei, E., Palumbo, A., Fusaro, M., Aldrovandi, A., Messalli, G., Tresoldi, S., Malagò, R., La Grutta, L., Runza, G., Brambilla, V., Tedeschi, C., Casolo, G., Midiri, M., and Mollet, N. R.

Published
2008
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41. Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study.

Author

Kirişli, H. A., Schaap, M., Klein, S., Papadopoulou, S. L., Bonardi, M., Chen, C. H., Weustink, A. C., Mollet, N. R., Vonken, E. J., van der Geest, R. J., van Walsum, T., and Niessen, W. J.

Subjects
CORONARY disease, DIAGNOSIS, TOMOGRAPHY, ANGIOGRAPHY, PERICARDIUM, QUANTITATIVE research, HEART ventricles, MEDICAL screening, IMAGE processing
Abstract

Purpose: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. Methods: A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. Results: The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94±1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26±1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. Conclusions: A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/multivendor data sets. [ABSTRACT FROM AUTHOR]

Published
2010
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42. Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach.

Author

Metz, C. T., Schaap, M., Weustink, A. C., Mollet, N. R., van Walsum, T., and Niessen, W. J.

Subjects
CORONARY disease, DIAGNOSIS, ANGIOGRAPHY, DIAGNOSTIC imaging, MEDICAL physics, ALGORITHMS
Abstract

Purpose: The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time. Methods: A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed. Results: The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel centerlines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images. Conclusions: The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research. [ABSTRACT FROM AUTHOR]

Published
2009
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