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

4 Citations (Scopus)

Abstract

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
DOIs
StatePublished - Dec 16 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
Volume7259
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2009 - Image Processing
CountryUnited States
CityLake Buena Vista, FL
Period2/8/092/10/09

Fingerprint

lungs
Lung
Pixels
pixels
fans
Fans

Keywords

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

ASJC Scopus subject areas

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

Cite this

Guo, S., & Fei, B. (2009). A minimal path searching approach for active shape model (ASM)-based segmentation of the lung. In Medical Imaging 2009 - Image Processing [72594B] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7259). https://doi.org/10.1117/12.812575

A minimal path searching approach for active shape model (ASM)-based segmentation of the lung. / Guo, Shengwen; Fei, Baowei.

Medical Imaging 2009 - Image Processing. 2009. 72594B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7259).

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

Guo, S & Fei, B 2009, A minimal path searching approach for active shape model (ASM)-based segmentation of the lung. in Medical Imaging 2009 - Image Processing., 72594B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 7259, Medical Imaging 2009 - Image Processing, Lake Buena Vista, FL, United States, 2/8/09. https://doi.org/10.1117/12.812575
Guo S, Fei B. A minimal path searching approach for active shape model (ASM)-based segmentation of the lung. In Medical Imaging 2009 - Image Processing. 2009. 72594B. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). https://doi.org/10.1117/12.812575
Guo, Shengwen ; Fei, Baowei. / A minimal path searching approach for active shape model (ASM)-based segmentation of the lung. Medical Imaging 2009 - Image Processing. 2009. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).
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