Resumen:
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Modeling the liver deformation forms the basis for the development of
new clinical applications that improve the diagnosis, planning and guidance
in liver surgery. However, the patient-specific modeling of this organ and ...[+]
Modeling the liver deformation forms the basis for the development of
new clinical applications that improve the diagnosis, planning and guidance
in liver surgery. However, the patient-specific modeling of this organ and its
validation are still a challenge in Biomechanics. The reason is the difficulty
to measure the mechanical response of the in vivo liver tissue. The current
approach consist of performing minimally invasive or open surgery aimed at
estimating the elastic constant of the proposed biomechanical models.
This dissertation presents how the use of medical image analysis and evolutionary
computation allows the characterization of the biomechanical behavior
of the liver, avoiding the use of these minimally invasive techniques. In particular,
the use of similarity coefficients commonly used in medical image analysis
has permitted, on one hand, to estimate the patient-specific biomechanical
model of the liver avoiding the invasive measurement of its mechanical response.
On the other hand, these coefficients have also permitted to validate
the proposed biomechanical models.
Jaccard coefficient and Hausdorff distance have been used to validate the
models proposed to simulate the behavior of ex vivo lamb livers, calculating
the error between the volume of the experimentally deformed samples of the
livers and the volume from biomechanical simulations of these deformations.
These coefficients has provided information, such as the shape of the samples
and the error distribution along their volume. For this reason, both coefficients
have also been used to formulate a novel function, the Geometric Similarity
Function (GSF). This function has permitted to establish a methodology to
estimate the elastic constants of the models proposed for the human liver using
evolutionary computation. Several optimization strategies, using GSF as cost
function, have been developed aimed at estimating the patient-specific elastic
constants of the biomechanical models proposed for the human liver.
Finally, this methodology has been used to define and validate a biomechanical
model proposed for an in vitro human liver.
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