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Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis

  • Michael Sass Hansen
  • Fei Zhao
  • Honghai Zhang
  • Nicholas E. Walker
  • Andreas Wahle
  • Thomas Scholz
  • Milan Sonka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4241)

Abstract

A computer-aided diagnosis (CAD) method is reported that allows the objective identification of subjects with connective tissue disorders from 3D aortic MR images using segmentation and independent component analysis (ICA). The first step to extend the model to 4D (3D + time) has also been taken. ICA is an effective tool for connective tissue disease detection in the presence of sparse data using prior knowledge to order the components, and the components can be inspected visually.

3D+time MR image data sets acquired from 31 normal and connective tissue disorder subjects at end-diastole (R-wave peak) and at 45% of the R-R interval were used to evaluate the performance of our method. The automated 3D segmentation result produced accurate aortic surfaces covering the aorta. The CAD method distinguished between normal and connective tissue disorder subjects with a classification accuracy of 93.5 %.

Keywords

Independent Component Analysis Independent Component Abdominal Aortic Aneurysm Segmentation Result Independent Component Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michael Sass Hansen
    • 1
    • 4
  • Fei Zhao
    • 1
  • Honghai Zhang
    • 1
  • Nicholas E. Walker
    • 2
  • Andreas Wahle
    • 1
  • Thomas Scholz
    • 3
  • Milan Sonka
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of IowaIowa CityUSA
  2. 2.Department of Internal MedicineUniversity of IowaIowa CityUSA
  3. 3.Department of PediatricsUniversity of IowaIowa CityUSA
  4. 4.Department of Informatics and Mathematical ModellingTechnical University of DenmarkLyngbyDenmark

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