Multiresolution active contour model applied on lung and colon images

Jamshid Dehmeshki; Musib Siddique; Wing Wong; Irina Chis Ster

doi:10.1117/12.535489

12 May 2004 Multiresolution active contour model applied on lung and colon images

Jamshid Dehmeshki, Musib Siddique, Wing Wong, Irina Chis Ster

Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.535489
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

This paper deploys a wavelet based scale-space approach to extract the boundary of the object of interest in medical CT images. The classical approach of the active contour models consists of starting with an initial contour, to deform it under the action of some forces attracting the contour towards the edges by means of a set of forces. The mathematical model involves in the minimisation of an objective function called energy functional, which depends on the geometry of the contour as well as of the image characteristics. Various strategies could be used for the formulation of the energy functional and its optimisation. In this study, a wavelet based scale-space approach has been adopted. The coarsest scale is able to enlarge the capture region surrounding an object and avoids the trapping of contour into weak edges. The finer scales are used to refine the contour as close as possible to the boundary of the object. An adaptive scale coefficient for the balloon energy has been introduced. Four levels of resolution have been applied in order to get reproducibility of the contour despite poor different initialisations. The scheme has been applied to segment the regions of interest in CT lung and colon images. The result has been shown to be accurate and reproducible for the cases containing fat, holes and other small high intensity objects inside lung nodules as well as colon polyps.

Citation Download Citation

Jamshid Dehmeshki, Musib Siddique, Wing Wong, and Irina Chis Ster "Multiresolution active contour model applied on lung and colon images", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535489

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