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Fast Anatomical Structure Localization Using Top-Down Image Patch Regression

  • René Donner
  • Bjoern H. Menze
  • Horst Bischof
  • Georg Langs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7766)

Abstract

Fully automatic localization of anatomical structures in 2D and 3D radiological data sets is important in both computer aided diagnosis, and the rapid automatic processing of large amounts of data. We present a simple, accurate and fast approach with low computational complexity to find anatomical landmarks, based on a multi-scale regression codebook of informative image patches and encoded landmark contexts.

From a set of annotated training volumes the method captures the appearance of landmarks over several scales together with relative positions of neighboring landmarks and a spatial distribution model. During multi-scale search in a target volume, starting from the coarsest level, each landmark model predicts all landmark positions it has encoded, with the median of all predictions yielding the final prediction for each scale.

We present results on two challenging data sets (hand radiographs and hand CTs), where our method achieves comparable accuracy to the state of the art with substantially improved run-time.

Keywords

Anatomical structure localization nearest neighbor regression image patch codebooks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • René Donner
    • 1
    • 2
  • Bjoern H. Menze
    • 3
    • 4
    • 5
  • Horst Bischof
    • 2
  • Georg Langs
    • 1
    • 3
  1. 1.Computational Image Analysis and Radiology Lab, Department of RadiologyMedical University ViennaAustria
  2. 2.Institute for Computer Graphics and VisionGraz University of TechnologyAustria
  3. 3.CSAILMITCambridgeUSA
  4. 4.Asclepios ProjectINRIA Sophia-AntipolisFrance
  5. 5.Computer Vision LaboratoryETH ZurichSwitzerland

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