Return
Adjoint Active Surfaces for Localization and Imaging
DOI:10.1109/TIP.2014.2374538.png)
Abstract
En 中文
This paper addresses the problem of localizing and segmenting regions embedded within a surrounding medium by characterizing their boundaries, as opposed to imaging the entirety of the volume. Active surfaces are used to directly reconstruct the shape of the region of interest. We describe the procedure for finding the optimal surface, which is computed iteratively via gradient descent that exploits the sensitivity of an error minimization functional to changes of the active surface. In doing so, we introduce the adjoint model to compute the sensitivity, and in this respect, the method shares common ground with several other disciplines, such as optimal control. Finally, we illustrate the proposed active surface technique in the framework of wave propagation governed by the scalar Helmholtz equation. Potential applications include electromagnetics, acoustics, geophysics, nondestructive testing, and medical imaging.
Keywords:
Image reconstruction
active shape model
reconstruction algorithms
level set
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
13.7
Papers:
1.0W
Citations:
8.4W

