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A Hybrid Method for Automatic Anatomical Variant Detection and Segmentation

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These file attachments have been under embargo and were made available to the public after the embargo was lifted on 19 July 2012.

Author: Lorenz, C. · Hanna, R. · Barschdorf, H. · Klinder, T. · Weber, IF. (Univ. Karlsruhe) · Krueger, M. (KIT) · Doessel, O. (Univ. Karlsruhe)
Type:Conference paper
Date:2012-07-19
Embargo lifted:2012-07-19
Publisher: Springer
Institution: Philips Research
Source:FIMH 2011: 6th International Conference on Functional Imaging and Modeling of the Heart, New York, USA, 25-27 May 2011, LNCC 6666; authors version
Identifier: MS 32.138
Keywords: anatomical variants · cardiac imaging · hybrid computer methods · left atrium · model-based segmentation
Rights: (c) Springer

Abstract

The delineation of anatomical structures in medical images can be achieved in an efficient and robust manner using statistical anatomical organ models, which has been demonstrated for an already considerable set of organs, including the heart. While it is possible to provide models with sufficient shape variability to cope, to a large extent, with inter-patient variability, as long as object topology is conserved, it is a fundamental problem to cope with topological organvariability. We address this by creating a set of model variants and selecting the most appropriate model variant for the patient at hand. We propose a hybrid method combining model-based image analysiswith a guided region growing approach for automated anatomical variant selection and apply it to the left atrium in cardiac CT images. Concerning the human heart, the left atrium is the most variable sub-structure with a variable number of pulmonary veins drainng into it.It is of large clinical interest in the context of atrial fibrillation and related interventions.

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