11,984 research outputs found
Image processing for plastic surgery planning
This thesis presents some image processing tools for plastic surgery planning. In particular,
it presents a novel method that combines local and global context in a probabilistic
relaxation framework to identify cephalometric landmarks used in Maxillofacial plastic
surgery. It also uses a method that utilises global and local symmetry to identify abnormalities
in CT frontal images of the human body. The proposed methodologies are
evaluated with the help of several clinical data supplied by collaborating plastic surgeons
Finsler Active Contours
©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TPAMI.2007.70713In this paper, we propose an image segmentation technique based on augmenting the conformal (or geodesic) active contour framework with directional information. In the isotropic case, the euclidean metric is locally multiplied by a scalar conformal factor based on image information such that the weighted length of curves lying on points of interest (typically edges) is small. The conformal factor that is chosen depends only upon position and is in this sense isotropic. Although directional information has been studied previously for other segmentation frameworks, here, we show that if one desires to add directionality in the conformal active contour framework, then one gets a well-defined minimization problem in the case that the factor defines a Finsler metric. Optimal curves may be obtained using the calculus of variations or dynamic programming-based schemes. Finally, we demonstrate the technique by extracting roads from aerial imagery, blood vessels from medical angiograms, and neural tracts from diffusion-weighted magnetic resonance imagery
A higher-order active contour model of a `gas of circles' and its application to tree crown extraction
Many image processing problems involve identifying the region in the image
domain occupied by a given entity in the scene. Automatic solution of these
problems requires models that incorporate significant prior knowledge about the
shape of the region. Many methods for including such knowledge run into
difficulties when the topology of the region is unknown a priori, for example
when the entity is composed of an unknown number of similar objects.
Higher-order active contours (HOACs) represent one method for the modelling of
non-trivial prior knowledge about shape without necessarily constraining region
topology, via the inclusion of non-local interactions between region boundary
points in the energy defining the model. The case of an unknown number of
circular objects arises in a number of domains, e.g. medical, biological,
nanotechnological, and remote sensing imagery. Regions composed of an a priori
unknown number of circles may be referred to as a `gas of circles'. In this
report, we present a HOAC model of a `gas of circles'. In order to guarantee
stable circles, we conduct a stability analysis via a functional Taylor
expansion of the HOAC energy around a circular shape. This analysis fixes one
of the model parameters in terms of the others and constrains the rest. In
conjunction with a suitable likelihood energy, we apply the model to the
extraction of tree crowns from aerial imagery, and show that the new model
outperforms other techniques
Hot-hole lasers in III-V semiconductors
Following the success of p-Ge hot-hole lasers, there is also potential for
using other semiconductor materials, notably III-V's such as GaAs and InSb.
Previous analysis had suggested that a large effective mass ratio between the
heavy and light holes is advantageous, which implies that InSb would make an
excellent hot-hole laser. Using our Monte Carlo simulations of both GaAs and
InSb hot-hole lasers in combination with a rate equation model, we see that
previously accepted criteria used to predict performance are not always
reliable, and we suggest suitable alternatives. The simulation results include
gain and gain bandwidth as a function of field strength and laser frequency,
and alternative field orientations and photon polarizations are considered.
Comparisons are made with bulk p-Ge systems. The optimum conditions predicted
by our simulations could then be used in the design of quantum-well hot-hole
lasers.Comment: 7 pages, 4 figures (8 frames
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