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Matching Endoscopic 3D Image Data with 4D Echocardiographic Data for Extended Reality Support in Mitral Valve Repair Surgery

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Bildverarbeitung für die Medizin 2023 (BVM 2023)

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Abstract

Minimally invasive mitral valve repair is a common cardiac surgery procedure. Combining intraoperative stereo-endoscopic images with pre-operative 4D transesophageal echocardiography (TEE) can support surgeons in correlating surgical interventions with the functional implications in the beating heart. We propose a method for registering 3D point clouds reconstructed from endoscopic images with TEE by extracting and matching anatomical landmarks and refining the registration using the Iterative Closest Point Algorithm. The applicability of our method is assessed by the computation time and the registration accuracy.

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References

  1. Jones EC, Devereux RB, Roman MJ, et al. Prevalence and correlates of mitral regurgitation in a population-based sample (the Strong Heart Study). Am J Cardiol. 2001;87(3):298–304.

    Google Scholar 

  2. Dziadzko V, Dziadzko M, Medina-Inojosa JR, Benfari G, et al. Causes and mechanisms of isolated mitral regurgitation in the community: clinical context and outcome. Eur Heart J. 2019;40(27):2194–202.

    Google Scholar 

  3. Beckmann A, Meyer R, Lewandowski J, et al. German Heart Surgery Report 2021: the annual updated registry of the German Society for Thoracic and Cardiovascular Surgery. Thorac Cardiovasc Surg. 2022;70(05):362–76.

    Google Scholar 

  4. Jacobs S, Sündermann SH. Minimally invasive valve sparing mitral valve repair—the loop technique—how we do it. Ann Cardiothorac Surg. 2013;2(6):818–24.

    Google Scholar 

  5. Nanchahal S, Arjomandi Rad A, Naruka V, et al. Mitral valve surgery assisted by virtual and augmented reality: cardiac surgery at the front of innovation. Perfusion. 2022.

    Google Scholar 

  6. Engelhardt S, De Simone R, Zimmermann N, et al. Augmented reality-enhanced endoscopic images for annuloplasty ring sizing. Augment Environ Comput Assist Interv (2014). Cham: Springer International, 2014:128–37.

    Google Scholar 

  7. Ender J, Končar-Zeh J, Mukherjee C, et al. Value of augmented reality-enhanced transesophageal echocardiography (TEE) for determining optimal annuloplasty ring size during mitral valve repair. Ann Thorac Surg. 2008;86(5):1473–8.

    Google Scholar 

  8. Ivantsits M, Tautz L, Sündermann S, et al. DL-based segmentation of endoscopic scenes for mitral valve repair. CDBME. 2020;6(1).

    Google Scholar 

  9. Andreassen BS, Völgyes D, Samset E, et al. Mitral annulus segmentation and anatomical orientation detection in TEE images using periodic 3D CNN. IEEE Access. 2022;10:51472–86.

    Google Scholar 

  10. Lowe DG. Distinctive image features from scale-invariant keypoints. Int J Comput Vis. 2004;60(2):91–110.

    Google Scholar 

  11. Muja M, Lowe DG. Fast approximate nearest neighbors with automatic algorithm configuration. VISAPP 2009. SciTePress, 2009:331–40.

    Google Scholar 

  12. Hirschmuller H. Stereo processing by semiglobal matching and mutual information. IEEE Trans Pattern Anal Mach Intell. 2008;30(2):328–41.

    Google Scholar 

  13. Arun KS, Huang TS, Blostein SD. Least-squares fitting of two 3-D point sets. IEEE Trans Pattern Anal Mach Intell. 1987;PAMI-9(5):698–700.

    Google Scholar 

  14. Bleyer M, Chambon S. Does color really help in dense stereo matching? 3DPVT 2010. 2010:1–8.

    Google Scholar 

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Correspondence to Juri Welz .

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© 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Welz, J. et al. (2023). Matching Endoscopic 3D Image Data with 4D Echocardiographic Data for Extended Reality Support in Mitral Valve Repair Surgery. In: Deserno, T.M., Handels, H., Maier, A., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2023. BVM 2023. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-41657-7_65

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