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TitleFast Segmentation of the Left Atrial Appendage in 3D Transesophageal Echocardiographic Images
Author(s)Morais, Pedro André Gonçalves
Queirós, Sandro Filipe Monteiro
Meester, Pieter De
Budts, Werner
Vilaça, João L.
Tavares, João Manuel R. S.
D'Hooge, Jan
KeywordsB-spline explicit active surface
curvilinear blind-ended model
left atrial appendage
three-dimensional (3-D) image segmentation
3D image segmentation
Image segmentation
Mathematical model
Splines (mathematics)
Three-dimensional displays
Issue dateDec-2018
JournalIEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
CitationMorais, P., Queirós, S., De Meester, P., Budts, W., Vilaça, J. L., Tavares, J. M. R., & D’hooge, J. (2018). Fast Segmentation of the Left Atrial Appendage in 3-D Transesophageal Echocardiographic Images. IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 65(12), 2332-2342
Abstract(s)Left atrial appendage (LAA) has been generally described as "our most lethal attachment," being considered the major source of thromboembolism in patients with nonvalvular atrial fibrillation. Currently, LAA occlusion can be offered as a treatment for these patients, obstructing the LAA through a percutaneously delivered device. Nevertheless, correct device sizing is not straightforward, requiring manual analysis of peri-procedural images. This approach is suboptimal, time demanding, and highly variable between experts, which can result in lengthy procedures and excess manipulations. In this paper, a semiautomatic LAA segmentation technique for 3-D transesophageal echocardiography (TEE) images is presented. Specifically, the proposed technique relies on a novel segmentation pipeline where a curvilinear blind-ended model is optimized through a double stage strategy: 1) fast contour evolution using global terms and 2) contour refinement based on regional energies. To reduce its computational cost, and thus make it more attractive to real interventions, the B-spline explicit active surface framework was used. This novel method was evaluated in a clinical database of 20 patients. Manual analysis performed by two observers was used as ground truth. The 3-D segmentation results corroborated the accuracy, robustness to the variation of the parameters, and computationally attractiveness of the proposed method, taking approximately 14 s to segment the LAA with an average accuracy of ~0.9 mm. Moreover, a performance comparable to the interobserver variability was found. Finally, the advantages of the segmented model were evaluated, while semiautomatically extracting the clinical measurements for device selection, showing a similar accuracy but with a higher reproducibility when compared to the current practice. Overall, the proposed segmentation method shows potential for an improved planning of LAA occlusion, demonstrating its added value for normal clinical practice.
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Appears in Collections:ICVS - Artigos em revistas internacionais / Papers in international journals

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