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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

01.02.2016 | Original Article

Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification

verfasst von: Cosmin Adrian Morariu, Tobias Terheiden, Daniel Sebastian Dohle, Konstantinos Tsagakis, Josef Pauli

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 2/2016

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Abstract

Purpose

Our goal is to provide precise measurements of the aortic dimensions in case of dissection pathologies. Quantification of surface lengths and aortic radii/diameters together with the visualization of the dissection membrane represents crucial prerequisites for enabling minimally invasive treatment of type A dissections, which always also imply the ascending aorta.

Methods

We seek a measure invariant to luminance and contrast for aortic outer wall segmentation. Therefore, we propose a 2D graph-based approach using phase congruency combined with additional features. Phase congruency is extended to 3D by designing a novel conic directional filter and adding a lowpass component to the 3D Log-Gabor filterbank for extracting the fine dissection membrane, which separates the true lumen from the false one within the aorta.

Results

The result of the outer wall segmentation is compared with manually annotated axial slices belonging to 11 CTA datasets. Quantitative assessment of our novel 2D/3D membrane extraction algorithms has been obtained for 10 datasets and reveals subvoxel accuracy in all cases. Aortic inner and outer surface lengths, determined within 2 cadaveric CT datasets, are validated against manual measurements performed by a vascular surgeon on excised aortas of the body donors.

Conclusions

This contribution proposes a complete pipeline for segmentation and quantification of aortic dissections. Validation against ground truth of the 3D contour lengths quantification represents a significant step toward custom-designed stent-grafts.

Avila-Montes OC, Kukure U, Kakadiaris IA (2010) Aorta segmentation in non-contrast cardiac CT images using an entropy-based cost function. In: SPIE medical imaging. International Society for Optics and Photonics, pp 76,233J–76,233J–8

Barber CB, Dobkin DP, Huhdanpaa H (1996) The quickhull algorithm for convex hulls. ACM Trans Math Softw (TOMS) 22(4):469–483CrossRef

Feuerstein M, Kitasaka T, Mori K (2009) Automated anatomical likelihood driven extraction and branching detection of aortic arch in 3-D chest CT. In: Second international workshop on pulmonary image analysis, pp 49–60

Hacihaliloglu I, Abugharbieh R, Hodgson AJ, Rohling RN, Guy P (2012) Automatic bone localization and fracture detection from volumetric ultrasound images using 3-D local phase features. Ultrasound Med Biol 38(1):128–144CrossRefPubMed

Kovács T, Cattin P, Alkadhi H, Wildermuth S, Székely G (2006) Automatic segmentation of the aortic dissection membrane from 3D CTA images. In: Medical imaging and augmented reality. Springer, New York, pp 317–324

Kovesi P (1999) Image features from phase congruency. Videre J Comput Vis Res 1(3):1–26

Krissian K, Carreira JM, Esclarin J, Maynar M (2014) Semi-automatic segmentation and detection of aorta dissection wall in MDCT angiography. Med Image Anal 18(1):83–102CrossRefPubMed

Kurugol S, San Jose Estepar R, Ross J, Washko GR (2012) Aorta segmentation with a 3D level set approach and quantification of aortic calcifications in non-contrast chest CT. In: 2012 annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp 2343–2346. IEEE

Morariu CA, Terheiden T, Dohle DS, Tsagakis K, Paul J (2014) Graph-based and variational minimization of statistical cost functionals for 3D segmentation of aortic dissections. In: Pattern recognition, vol 8753, pp 511–522. Springer LNCS

10.

Perona P, Malik J (1990) Scale-space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12(7):629–639CrossRef

11.

Powers DM (2011) Evaluation: from precision, recall and F-measure to ROC, informedness, markedness & correlation. J Mach Learn Technol 2(1):37–63

12.

Wendt D, Thielmann M, Melzer A, Benedik J, Droc I, Tsagakis K, Dohle DS, Jakob H, Abele JE (2013) The past, present and future of minimally invasive therapy in endovascular interventions: a review and speculative outlook. Minim Invasive Ther Allied Technol 22(4):242–253CrossRefPubMed

13.

Wörz S, von Tengg-Kobligk H, Henninger V, Rengier F, Schumacher H, Böckler D, Kauczor HU, Rohr K (2010) 3-D quantification of the aortic arch morphology in 3-D CTA data for endovascular aortic repair. IEEE Trans Biomed Eng 57(10):2359–2368CrossRefPubMed

Titel: Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification
verfasst von: Cosmin Adrian Morariu
Tobias Terheiden
Daniel Sebastian Dohle
Konstantinos Tsagakis
Josef Pauli
Publikationsdatum: 01.02.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 2/2016
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-015-1283-1

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Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification