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Displacement Estimation Analyses (Paperback)
Loot Price: R2,002
Discovery Miles 20 020
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Displacement Estimation Analyses (Paperback)
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Measuring the mechanical properties of human soft tissue is a
current topic in the field of diagnostic ultrasound research. Long
before ultrasound was used in medical diagnosis, palpation was the
important clinical examination method, and was practiced by the
ancient Egyptians about 5000 years ago. Palpation is still one of
the standard examination methods performed in the modern diagnosis
for the detection of inter alia breast and prostate abnormalities,
because the change of the pathological state of tissue is often
correlated with changes in stiffness; in particular some malignant
tumors are significantly stiffer and less mobile than surrounding
healthy tissue. However, the use of conventional imaging techniques
such as, computer tomography, magnet resonance tomography and
ultrasound, for the medical diagnosis is not directly able to
measure the mechanical properties of tissue. In this work, a new
imaging modality was developed which can be additionally used for
the careful assessment of tumors in different soft tissues. This
novel modality was named reconstructive ultrasound elastography,
which is regarded as an objective imaging method not limited to
small deformations and complements the manual palpation procedure
for medical diagnostics. In order to obtain noninvasively
quantitative mechanical properties of tissue, we proposed a new
algorithm by which the spatial distribution of the relative shear
modulus of tissue can be estimated from the measured deformation.
From the measured displacement field the relative shear modulus
distribution in the examined object can be determined in the sense
of an ill-posed inverse problem. Due to the existing large
deformations an algorithm wasdeveloped for the solution of the
inverse problem on the basis of the nonlinear elasticity theory.
The efficiency of the developed algorithm was shown using samples
of poly vinyl alcohol phantoms, as well as in vivo data computed
from prostate-cancer cases and compared to the histology data.
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