Abstract
Accurate definition of a three-dimensional (3D) branching tree structures from large 3D medical images has become a common problem over several imaging modalities. For example, 3D computed-tomography (CT) images of the airways as well as micro-CT images of vasculature employ new paradigms that require detailed definitions of tree structures. Manual definition is impossible for images of this scale. Existing techniques lack features necessary for navigational or quantitative analysis or fail to recover paths. We present a generic tree analysis technique that is applicable to arbitrary segmented images of branching structures for both of these purposes. The method has been tested on over 30 human, anumal, phantom, and micro-CT images. An initial comparison with a previous method demonstrates its ability to capture more paths, especially in peripheral regions.
Original language | English (US) |
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Pages | II/333-II/336 |
State | Published - 2002 |
Event | International Conference on Image Processing (ICIP'02) - Rochester, NY, United States Duration: Sep 22 2002 → Sep 25 2002 |
Other
Other | International Conference on Image Processing (ICIP'02) |
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Country/Territory | United States |
City | Rochester, NY |
Period | 9/22/02 → 9/25/02 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering