157 research outputs found
Locally Orderless Registration
Image registration is an important tool for medical image analysis and is
used to bring images into the same reference frame by warping the coordinate
field of one image, such that some similarity measure is minimized. We study
similarity in image registration in the context of Locally Orderless Images
(LOI), which is the natural way to study density estimates and reveals the 3
fundamental scales: the measurement scale, the intensity scale, and the
integration scale.
This paper has three main contributions: Firstly, we rephrase a large set of
popular similarity measures into a common framework, which we refer to as
Locally Orderless Registration, and which makes full use of the features of
local histograms. Secondly, we extend the theoretical understanding of the
local histograms. Thirdly, we use our framework to compare two state-of-the-art
intensity density estimators for image registration: The Parzen Window (PW) and
the Generalized Partial Volume (GPV), and we demonstrate their differences on a
popular similarity measure, Normalized Mutual Information (NMI).
We conclude, that complicated similarity measures such as NMI may be
evaluated almost as fast as simple measures such as Sum of Squared Distances
(SSD) regardless of the choice of PW and GPV. Also, GPV is an asymmetric
measure, and PW is our preferred choice.Comment: submitte
Information-Theoretic Registration with Explicit Reorientation of Diffusion-Weighted Images
We present an information-theoretic approach to the registration of images
with directional information, and especially for diffusion-Weighted Images
(DWI), with explicit optimization over the directional scale. We call it
Locally Orderless Registration with Directions (LORD). We focus on normalized
mutual information as a robust information-theoretic similarity measure for
DWI. The framework is an extension of the LOR-DWI density-based hierarchical
scale-space model that varies and optimizes the integration, spatial,
directional, and intensity scales. As affine transformations are insufficient
for inter-subject registration, we extend the model to non-rigid deformations.
We illustrate that the proposed model deforms orientation distribution
functions (ODFs) correctly and is capable of handling the classic complex
challenges in DWI-registrations, such as the registration of fiber-crossings
along with kissing, fanning, and interleaving fibers. Our experimental results
clearly illustrate a novel promising regularizing effect, that comes from the
nonlinear orientation-based cost function. We show the properties of the
different image scales and, we show that including orientational information in
our model makes the model better at retrieving deformations in contrast to
standard scalar-based registration.Comment: 16 pages, 19 figure
Higher-Order Momentum Distributions and Locally Affine LDDMM Registration
To achieve sparse parametrizations that allows intuitive analysis, we aim to
represent deformation with a basis containing interpretable elements, and we
wish to use elements that have the description capacity to represent the
deformation compactly. To accomplish this, we introduce in this paper
higher-order momentum distributions in the LDDMM registration framework. While
the zeroth order moments previously used in LDDMM only describe local
displacement, the first-order momenta that are proposed here represent a basis
that allows local description of affine transformations and subsequent compact
description of non-translational movement in a globally non-rigid deformation.
The resulting representation contains directly interpretable information from
both mathematical and modeling perspectives. We develop the mathematical
construction of the registration framework with higher-order momenta, we show
the implications for sparse image registration and deformation description, and
we provide examples of how the parametrization enables registration with a very
low number of parameters. The capacity and interpretability of the
parametrization using higher-order momenta lead to natural modeling of
articulated movement, and the method promises to be useful for quantifying
ventricle expansion and progressing atrophy during Alzheimer's disease
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Customized design of hearing aids using statistical shape learning
3D shape modeling is a crucial component of rapid prototyping systems
that customize shapes of implants and prosthetic devices to a patient’s
anatomy. In this paper, we present a solution to the problem of customized 3D
shape modeling using a statistical shape analysis framework. We design a novel
method to learn the relationship between two classes of shapes, which are related
by certain operations or transformation. The two associated shape classes are
represented in a lower dimensional manifold, and the reduced set of parameters
obtained in this subspace is utilized in an estimation, which is exemplified by a
multivariate regression in this paper.We demonstrate our method with a felicitous
application to estimation of customized hearing aid devices
A multi-patient analysis of the center of rotation trajectories using finite element models of the human mandible
Studying different types of tooth movements can help us to better understand
the force systems used for tooth position correction in orthodontic treatments.
This study considers a more realistic force system in tooth movement modeling
across different patients and investigates the effect of the couple force
direction on the position of the center of rotation (CRot). The finite-element
(FE) models of human mandibles from three patients are used to investigate the
position of the CRots for different patients' teeth in 3D space. The CRot is
considered a single point in a 3D coordinate system and is obtained by choosing
the closest point on the axis of rotation to the center of resistance (CRes). A
force system, consisting of a constant load and a couple (pair of forces), is
applied to each tooth, and the corresponding CRot trajectories are examined
across different patients. To perform a consistent inter-patient analysis,
different patients' teeth are registered to the corresponding reference teeth
using an affine transformation. The selected directions and applied points of
force on the reference teeth are then transformed into the registered teeth
domains. The effect of the direction of the couple on the location of the CRot
is also studied by rotating the couples about the three principal axes of a
patient's premolar. Our results indicate that similar patterns can be obtained
for the CRot positions of different patients and teeth if the same load
conditions are used. Moreover, equally rotating the direction of the couple
about the three principal axes results in different patterns for the CRot
positions, especially in labiolingual direction. The CRot trajectories follow
similar patterns in the corresponding teeth, but any changes in the direction
of the force and couple cause misalignment of the CRot trajectories, seen as
rotations about the long axis of the tooth
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