A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

Shengwen Guo, Baowei Fei

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

5 Scopus citations


We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2009 - Image Processing
StatePublished - 2009
Externally publishedYes
EventMedical Imaging 2009 - Image Processing - Lake Buena Vista, FL, United States
Duration: Feb 8 2009Feb 10 2009

Publication series

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


OtherMedical Imaging 2009 - Image Processing
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Deformable model
  • Digital radiographs
  • Minimal path
  • Segmentation
  • Statistical shape model

ASJC Scopus subject areas

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


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