학술논문

Multiscale medial shape-based analysis of image objects
Document Type
Periodical
Source
Proceedings of the IEEE Proc. IEEE Proceedings of the IEEE. 91(10):1670-1679 Oct, 2003
Subject
General Topics for Engineers
Engineering Profession
Aerospace
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Geoscience
Nuclear Engineering
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Photonics and Electrooptics
Image analysis
Image segmentation
Blood vessels
Biomedical imaging
Atomic measurements
Shape measurement
Shape control
Tail
Geometry
Image sequence analysis
Language
ISSN
0018-9219
1558-2256
Abstract
Medial representation of a three-dimensional (3-D) object or an ensemble of 3-D objects involves capturing the object interior as a locus of medial atoms, each atom being two vectors of equal length joined at the tail at the medial point. Medial representation has a variety of beneficial properties, among the most important of which are 1) its inherent geometry, provides an object-intrinsic coordinate system and thus provides correspondence between instances of the object in and near the object(s); 2) it captures the object interior and is, thus, very suitable for deformation; and 3) it provides the basis for an intuitive object-based multiscale sequence leading to efficiency of segmentation algorithms and trainability of statistical characterizations with limited training sets. As a result of these properties, medial representation is particularly suitable for the following image analysis tasks; how each operates will be described and will be illustrated by results: segmentation of objects and object complexes via deformable models; segmentation of tubular trees, e.g., of blood vessels, by following height ridges of measures of fit of medial atoms to target images; object-based image registration via medial loci of such blood vessel trees; statistical characterization of shape differences between control and pathological classes of structures. These analysis tasks are made possible by a new form of medial representation called m-reps, which is described.