Fully automatic segmentation of complex organ systems: example of trachea, esophagus and heart segmentation in CT images

Carsten Meyer; Jochen Peters; Jürgen Weese

doi:10.1117/12.877247

11 March 2011 Fully automatic segmentation of complex organ systems: example of trachea, esophagus and heart segmentation in CT images

Carsten Meyer, Jochen Peters, Jürgen Weese

Author Affiliations +

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 796216 (2011) https://doi.org/10.1117/12.877247
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Automatic segmentation is a prerequisite to efficiently analyze the large amount of image data produced by modern imaging modalities. Many algorithms exist to segment individual organs or organ systems. However, new clinical applications and the progress in imaging technology will require the segmentation of more and more complex organ systems composed of a number of substructures, e.g., the heart, the trachea, and the esophagus. The goal of this work is to demonstrate that such complex organ systems can be successfully segmented by integrating the individual organs into a general model-based segmentation framework, without tailoring the core adaptation engine to the individual organs. As an example, we address the fully automatic segmentation of the trachea (around its main bifurcation, including the proximal part of the two main bronchi) and the esophagus in addition to the heart with all chambers and attached major vessels. To this end, we integrate the trachea and the esophagus into a model-based cardiac segmentation framework. Specifically, in a first parametric adaptation step of the segmentation workflow, the trachea and the esophagus share global model transformations with adjacent heart structures. This allows to obtain a robust, approximate segmentation for the trachea even if it is only partly inside the field-of-view, and for the esophagus in spite of limited contrast. The segmentation is then refined in a subsequent deformable adaptation step. We obtained a mean segmentation error of about 0.6mm for the trachea and 2.3mm for the esophagus on a database of 23 volumetric cardiovascular CT images. Furthermore, we show by quantitative evaluation that our integrated framework outperforms individual esophagus segmentation, and individual trachea segmentation if the trachea is only partly inside the field-of-view.

Citation Download Citation

Carsten Meyer, Jochen Peters, and Jürgen Weese "Fully automatic segmentation of complex organ systems: example of trachea, esophagus and heart segmentation in CT images", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796216 (11 March 2011); https://doi.org/10.1117/12.877247

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