Project Details
Abstract
Cephalometry has been well accepted as a radiographic technique for portraying the
human head in terms of measurable geometry. It can be employed to depict the craniofacial
morphology of a side, e.g., frontal or lateral, and to study the bony structure of the face for
diagnosis, treatment planning/evaluation, and growth prediction and monitoring. The
inherent limitation of cephalometry is, however, its two-dimensional nature which exhibits
great variability in relationship measurements of cephalometric landmarks, such as the
distance between gnathion and zygomaticotemporal points. Three-dimensional craniofacial
imaging presents more promising and reliable measurements, and thus three-dimensional
craniofacial reconstruction (3D-CFR). It may take multiple cephalometric images of
different sides, determine the features that match and then perform alignment, and construct
the corresponding three-dimensional surface of the face. With help of computed tomography
(CT) and magnetic resonance imaging (MRI) technology, both the surface and the
underlying hard tissue can be captured and visualized in three dimension.
In this project, we propose computerized methods to perform image segmentation,
feature extraction, landmark matching and identification, three-dimensional reconstruction
from two-dimensional images of cephalometry or surface scan, and visualization. Several
image segmentation techniques, such as symmetric region grow, mean shift, level set
modeling, etc., will be examined and implemented. An improved robust and fast iterative
closest point (ICP) algorithm will be proposed to hierarchically match and identify rigid and
non-rigid cephalometric landmarks. We shall build a software platform to accommodate the
implemented methods as components. Components are grouped together to perform certain
task and is archived in a configuration script that records the sequence of the process and the
corresponding parameter settings.
The project will be carried out in three years. In the first year, we shall build the
infrastructure and prototype of the software platform that enables the users to perform
interactive manipulation and matching of two-dimensional cephalometric landmarks.
Fundamental object-oriented image processing and analysis components are available in the
first year. Late in the first year and in most of the second year, we shall realize the algorithms
of symmetric region grow, level set modeling, mean shift, and semi-automatic extraction of
features. All of these methods also serve as components that can be easily plugged into the
proposed software platform. At the same time, development of the same components on
Amira proceeds in parallel. Such additional implementation will facilitate the comparison of
the proposed platform with the commercial Amira. Late in the second year and in most of
the third year, we shall realize the improved ICP, perform matching and identification
between images over time, or images from the normal and abnormal. Later in the third year,
we shall perform unit/integration/system testing on the components and software platform
with realistic image data in hope to disclose random errors and make system refinement. The
scalability of the (component-based) software platform is also one of our major emphases to
assure usability for further research on more biological and medical/clinical applications.
Project IDs
Project ID:PB9801-2178
External Project ID:NSC97-2221-E182-037-MY3
External Project ID:NSC97-2221-E182-037-MY3
Status | Finished |
---|---|
Effective start/end date | 01/08/09 → 31/07/10 |
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