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Density and Attachment Agnostic CT Pulmonary Nodule Segmentation with Competition-Diffusion and New Morphological Operators

  • Toshiro KubotaEmail author
  • Anna K. Jerebko
  • Maneesh Dewan
  • Marcos Salganicoff
  • Arun Krishnan
Chapter

Abstract

Pulmonary nodules are potential manifestations of lung cancer, and their detection and inspection are essential for screening and diagnosis of the disease. The growth of a nodule is considered one of the most important cues for assessing its malignancy. Hence, the ability to segment the nodules accurately and measure their growth over time is crucial for prognosis. Accurate nodule segmentation is also vital for drug therapy development. A segmentation that can provide a consistent, reproducible, and accurate volumetric measure of nodule shrinkage/growth is very critical for evaluating the effectiveness of drug treatments

Keywords

Segmentation Algorithm Pulmonary Nodule Medial Axis Manual Segmentation Seed Point 
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 Science+Business Media, LLC 2011

Authors and Affiliations

  • Toshiro Kubota
    • 1
    Email author
  • Anna K. Jerebko
  • Maneesh Dewan
  • Marcos Salganicoff
  • Arun Krishnan
  1. 1.Department of Mathematical SciencesSusquehanna UniversitySelinsgroveUSA

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