Combining “Vertical” and “Horizontal” Features from Medical Images

  • Fred L. Bookstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 905)


Landmark points, when they can be located reliably over a sample of medical images, serve both to generate a feature space of biometric “shape variables” and also to specify an unwarping by which variation of pixel values associated with displacements of the landmarks can be corrected with respect to all landmarks simultaneously. There thus arise two separate spaces of descriptors, the “horizontal” and the “vertical.” Combinations of features from this pair of spaces for prediction or discrimination can be visualized in one or the other space alone by injecting precisely calibrated crosstalk between these channels. This essay analyzes a set of brain images in this way to highlight the effect of schizophrenia upon anatomy in the midsagittal plane.


Landmark Point Midsagittal Plane Landmark Configuration Biometric Analysis Graphic Overlay 
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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  3. Bookstein, F., Green, W.: Edgewarp: A flexible program package for biometric image warping in two dimensions. In R. Robb, ed., Visualization in Biomedical Computing 1994. SPIE Proceedings, volume 2359, 1994, pp. 135–147.Google Scholar
  4. Thatcher, R., Hallett, M., Zeffiro, T., John, E., Huerta, M., eds.: Functional Neuroimaging: Technical Foundations. Academic Press, 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Fred L. Bookstein
    • 1
  1. 1.University of MichiganAnn ArborUSA

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