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Fuzzy Segmentation of the Left Ventricle in Cardiac MRI Using Physiological Constraints

  • Tasos PapastylianouEmail author
  • Christopher Kelly
  • Benjamin Villard
  • Erica Dall’ Armellina
  • Vicente Grau
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)

Abstract

We describe a general framework for adapting existing segmentation algorithms, such that the need for optimisation of intrinsic, potentially unintuitive parameters is minimized, focusing instead on applying intuitive physiological constraints. This allows clinicians to easily influence existing tools of their choice towards outcomes with physiological properties that are more relevant to their particular clinical contexts, without having to deal with the optimisation specifics of a particular algorithm’s intrinsic parameters. This is achieved by a structured exploration of the parameter space resulting in a subspace of relevant segmentations, and by subsequent fusion biased towards segmentations that best adhere to the imposed constraints. We demonstrate this technique on an algorithm used by a validated, and freely available cardiac segmentation suite (Segmenthttp://segment.heiberg.se).

Keywords

cineMRI Heart Probabilistic Segmentation  

Abbreviations

MRI

Magnetic Resonance Imaging

CT

Computed Tomography

SSFP

Steady-State Free Precession

LGE

Late Gadolinium Enhancement

EF

Ejection Fraction

SV

Stroke Volume

SA

Short Axis

LV

Left Ventricle

PCA

Percutaneous Coronary Angioplasty

MI

Myocardial Infract

Notes

Acknowledgements

TP and BV acknowledge the support of the RCUK Digital Economy Programme grant number EP/G036861/1 (Oxford Centre for Doctoral Training in Healthcare Innovation). VG is supported by a BBSRC grant (BB/I012117/1), an EPSRC grant (EP/J013250/1) and by BHF New Horizon Grant NH/13/30238.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Tasos Papastylianou
    • 1
    Email author
  • Christopher Kelly
    • 1
  • Benjamin Villard
    • 1
  • Erica Dall’ Armellina
    • 2
  • Vicente Grau
    • 1
  1. 1.Institute of Biomedical EngineeringUniversity of OxfordOxfordUK
  2. 2.Acute Vascular Imaging CentreJohn Radcliffe HospitalOxfordUK

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