Spatio-temporal analysis tool for modeling pulmonary nodules in MR images

Li Shen, Heng Huang, James Ford, Chia Hsin Lu, Ling Gao, Wei Zheng, Fillia Makedon, Justin Pearlman

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

1 Scopus citations

Abstract

To detect lung cancer at an earlier stage, a promising method is to apply perfusion magnetic resonance imaging (pMRI) modified to assess tumor angiogenesis. One key issue is to effectively characterize angiogenic patterns of pulmonary nodules. Based on our previous study addressing this issue, in this work, we develop STAT, a Spatio-Temporal Analysis Tool that implements not only our previously proposed pulmonary nodule modeling framework but also a user friendly interface and many extended functions. Our goal is to make STAT an easy-to-use tool that can be applied to more general cases. STAT employs the following overall strategy for modeling pulmonary nodules: (1) nodule identification using a correlation maximization method, (2) nodule segmentation using edge detection, morphological operations and model-based strategy, and (3) nodule registration using landmark approach and thin-plate spline interpolation. In nodule identification, STAT provides new schemes for selecting the template and refining results in difficult cases. In nodule segmentation, STAT provides additional flexibilities for creating the weighting mask, selecting morphological structure elements and individually fixing segmentation result. In nodule registration, our previous study uses principal component analysis for landmark extraction, which may not work in general. To overcome this limitation, STAT provides an enhanced approach that minimizes the bending energy of the thin plate spline interpolation or mean square distance between each landmark set and the template set. Our main application of STAT is to define blood arrival patterns in the lung to identify tumor angiogenesis as a means of early accurate diagnosis of cancer.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2006
Subtitle of host publicationVisualization, Image-Guided Procedures, and Display
DOIs
StatePublished - Jun 30 2006
Externally publishedYes
EventMedical Imaging 2006: Visualization, Image-Guided Procedures, and Display - San Diego, CA, United States
Duration: Feb 12 2006Feb 14 2006

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6141
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2006: Visualization, Image-Guided Procedures, and Display
CountryUnited States
CitySan Diego, CA
Period2/12/062/14/06

Keywords

  • Perfusion MRI
  • Pulmonary nodule
  • Registration
  • Segmentation

ASJC Scopus subject areas

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

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  • Cite this

    Shen, L., Huang, H., Ford, J., Lu, C. H., Gao, L., Zheng, W., Makedon, F., & Pearlman, J. (2006). Spatio-temporal analysis tool for modeling pulmonary nodules in MR images. In Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display [61412I] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6141). https://doi.org/10.1117/12.654469