Conference proceeding
Object class uncertainty induced snake with applications to medical image segmentation
Proceedings of SPIE, Vol.5370(1), pp.369-380
Medical Imaging 2004: Image Processing
05/12/2004
DOI: 10.1117/12.535547
Abstract
Object segmentation is of paramount interest in many medical imaging applications. Among others, "snake"-an "active contour"-is a popular boundary-based segmentation framework where a spline is continuously deformed to lock onto an object boundary. The dynamics of a snake is governed by different internal and external forces. A major limitation of this framework has been the difficulty in using object-intensity driven features into snake dynamics which may prevent uncontrolled expansion/contraction once the snake leaks through a weak boundary region. In this paper, object-intensity force is effectively introduced into the snake-model using class uncertainty theory. Given a priori knowledge of object/background intensity distributions, class uncertainty yields object/background class of any location and establishes the confidence level of the classification. This confidence level has previously been demonstrated to be high inside the object/background regions and low near boundaries with intermediate intensities. This class uncertainty information adds an expanding (outward) force at locations pertaining to intensity-based object class and a squeezing (inward) force inside background regions. Consequently, the method possesses potential to resist an uncontrolled expansion of the snake (for an expanding type) into the background through a weak boundary while reducing the effect of this force near the boundary using the confidence information. The theory of object class uncertainty induced snake is developed and an implementation with efficient graphical interface is achieved. Preliminary results of application of the proposed snake approach on different images are presented and comparisons with conventional snake approaches are demonstrated.
Details
- Title: Subtitle
- Object class uncertainty induced snake with applications to medical image segmentation
- Creators
- Bipul Das - University of PennsylvaniaPunam K Saha - University of PennsylvaniaFelix W Wehrli - University of Pennsylvania
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5370(1), pp.369-380
- Conference
- Medical Imaging 2004: Image Processing
- DOI
- 10.1117/12.535547
- ISSN
- 0277-786X
- Language
- English
- Date published
- 05/12/2004
- Academic Unit
- Electrical and Computer Engineering; Radiology
- Record Identifier
- 9984197444802771
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