Learning discriminative distance functions for valve retrieval and improved decision support in valvular heart disease

Voigt I, Vitanovski D, Ionasec RI, Tsymbal A, Georgescu B, Zhou SK, Huber M, Navab N, Hornegger J, Comaniciu D (2010)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2010

Journal

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Original Authors: Voigt I., Vitanovski D., Ionasec R., Tsymal A., Georgescu B., Zhou S., Huber M., Navab N., Hornegger J., Comaniciu D.

Book Volume: 7623

Pages Range: -

Event location: San Diego, CA

Journal Issue: null

DOI: 10.1117/12.843972

Abstract

Disorders of the heart valves constitute a considerable health problem and often require surgical intervention. Recently various approaches were published seeking to overcome the shortcomings of current clinical practice,that still relies on manually performed measurements for performance assessment. Clinical decisions are still based on generic information from clinical guidelines and publications and personal experience of clinicians. We present a framework for retrieval and decision support using learning based discriminative distance functions and visualization of patient similarity with relative neighborhood graphsbased on shape and derived features. We considered two learning based techniques, namely learning from equivalence constraints and the intrinsic Random Forest distance. The generic approach enables for learning arbitrary user-defined concepts of similarity depending on the application. This is demonstrated with the proposed applications, including automated diagnosis and interventional suitability classification, where classification rates of up to 88.9% and 85.9% could be observed on a set of valve models from 288 and 102 patients respectively. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Authors with CRIS profile

Ingmar Voigt Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) Joachim Hornegger Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)

Involved external institutions

Siemens AG, Sector Corporate Technology DE Germany (DE) Siemens Corporate Research US United States (USA) (US) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Voigt, I., Vitanovski, D., Ionasec, R.I., Tsymbal, A., Georgescu, B., Zhou, S.K.,... Comaniciu, D. (2010). Learning discriminative distance functions for valve retrieval and improved decision support in valvular heart disease. In Proceedings of the Medical Imaging 2010: Image Processing (pp. -). San Diego, CA.

MLA:

Voigt, Ingmar, et al. "Learning discriminative distance functions for valve retrieval and improved decision support in valvular heart disease." Proceedings of the Medical Imaging 2010: Image Processing, San Diego, CA 2010. -.

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