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Shape Prior Based Myocardial Segmentation with Anatomically Motivated Pose Model

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Image Analysis and Processing. ICIAP 2022 Workshops (ICIAP 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13373))

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Abstract

We extend the shape-prior based geometric approach developed for myocardial segmentation in cardiac CT imagery by incorporating minimal user input in the form of anatomical constraints to guide the segmentation process resulting in significantly improved results. The shape-prior based geometric approach involves estimating coefficients of a low-dimensional principal component analysis based shape representation along with a set of rigid 3D pose parameters of three separate surfaces corresponding to left (LV)/right (RV) ventricles and Epicardium (Epi) by optimizing a novel Chan-Vese like image appearance model with gradient descent. We enhance this framework by allowing experienced clinical users to identify the centers of the three anatomies in apical slices and a common anatomical cardiac base slice. We integrate this minimal user input as anatomical constraints in the segmentation process by replacing the rigid 3D pose model with a novel blended model which incorporates rigidity only within 2D slices while incorporating non-rigid effects of shear and torsion along the third (axial) dimension. With this new formulation we achieved significantly improved segmentation results in terms of average symmetric surface-to-surface distances (mm): LV 1.05 ± 0.27; RV 1.7 ± 0.40; Epi 1.22 ± 0.56 compared to LV 2.3 ± 0.50; RV 1.13 ± 0.21; Epi 3.3 ± 0.50 with rigid 3D pose model.

This work was supported by the National Institutes of Health (NIH) grant number R01-HL-143350.

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Notes

  1. 1.

    These penalties are experimentally determined for each case. Typically, in some cases RV and Myo penalties need to be tuned to allow proper segmentation of RV in extreme poor contrast cases while LV (\(=0.5\)) and BG (\(=1.0\)) penalties remain fixed.

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Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Navdeep Dahiya & Anthony Yezzi

  2. Emory University, Atlanta, GA, 30322, USA

    Marina Piccinelli & Ernest Garcia

Authors
  1. Navdeep Dahiya
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  2. Marina Piccinelli
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  3. Ernest Garcia
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  4. Anthony Yezzi
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Correspondence to Navdeep Dahiya .

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Editors and Affiliations

  1. National Research Council, Lecce, Italy

    Pier Luigi Mazzeo

  2. Università Politecnica delle Marche, Ancona, Italy

    Emanuele Frontoni

  3. Boston University, Boston, MA, USA

    Stan Sclaroff

  4. National Research Council, Lecce, Italy

    Cosimo Distante

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Dahiya, N., Piccinelli, M., Garcia, E., Yezzi, A. (2022). Shape Prior Based Myocardial Segmentation with Anatomically Motivated Pose Model. In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022. Lecture Notes in Computer Science, vol 13373. Springer, Cham. https://doi.org/10.1007/978-3-031-13321-3_30

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  • DOI: https://doi.org/10.1007/978-3-031-13321-3_30

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