Automated segmentation of pulmonary nodule depicted on CT images

Jiantao Pu, Jun Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this study, an efficient computational geometry approach is introduced to segment pulmonary nodules. The basic idea is to estimate the three-dimensional surface of a nodule in question by analyzing the shape characteristics of its surrounding tissues in geometric space. Given a seed point or a specific location where a suspicious nodule may be, three steps are involved in this approach. First, a sub-volume centered at this seed point is extracted and the contained anatomy structures are modeled in the form of a triangle mesh surface. Second, a "visibility" test combined with a shape classification algorithm based on principal curvature analysis removes surfaces determined not to belong to nodule boundaries by specific rules. This step results in a partial surface of a nodule boundary. Third, an interpolation / extrapolation based shape reconstruction procedure is used to estimate a complete nodule surface by representing the partial surface as an implicit function. The preliminary experiments on 158 annotated CT examinations demonstrated that this scheme could achieve a reasonable performance in nodule segmentation.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2011
Subtitle of host publicationComputer-Aided Diagnosis
DOIs
StatePublished - May 13 2011
EventMedical Imaging 2011: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: Feb 15 2011Feb 17 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7963
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2011: Computer-Aided Diagnosis
CountryUnited States
CityLake Buena Vista, FL
Period2/15/112/17/11

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Keywords

  • Computer-aided Detection (CAD)
  • Lung Nodule
  • Segmentation
  • Shape analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Pu, J., & Tan, J. (2011). Automated segmentation of pulmonary nodule depicted on CT images. In Medical Imaging 2011: Computer-Aided Diagnosis [79632Z] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7963). https://doi.org/10.1117/12.878038