Abstract: Human soft tissue is loaded and deformed by any
activity, an effect known as a stress-strain relationship, and is often
described by a load and tissue elongation curve. Several advances
have been made in the fields of biology and mechanics of soft human
tissue. However, there is limited information available on in vivo
tissue mechanical characteristics and behavior. Confident mechanical
properties of human soft tissue cannot be extrapolated from e.g.
animal testing. Thus, there is need for non invasive methods to
analyze mechanical characteristics of soft human tissue. In the present
study, the internal mechanical conditions of the lower limb, which
is subject to an external load, is studied by use of the finite element
method. A detailed finite element model of the lower limb is made
possible by use of MRI scans. Skin, fat, bones, fascia and muscles
are represented separately and the material properties for them are
obtained from literature. Previous studies have been shown to address
macroscopic deformation features, e.g. indentation depth, to a large
extent. However, the detail in which the internal anatomical features
have been modeled does not reveal the critical internal strains that
may induce hypoxia and/or eventual tissue damage. The results of the
present study reveals that lumped material models, i.e. averaging of
the material properties for the different constituents, does not capture
regions of critical strains in contrast to more detailed models.
Abstract: Diffuse Optical Tomography (DOT) is a non-invasive imaging modality used in clinical diagnosis for earlier detection of carcinoma cells in brain tissue. It is a form of optical tomography which produces gives the reconstructed image of a human soft tissue with by using near-infra-red light. It comprises of two steps called forward model and inverse model. The forward model provides the light propagation in a biological medium. The inverse model uses the scattered light to collect the optical parameters of human tissue. DOT suffers from severe ill-posedness due to its incomplete measurement data. So the accurate analysis of this modality is very complicated. To overcome this problem, optical properties of the soft tissue such as absorption coefficient, scattering coefficient, optical flux are processed by the standard regularization technique called Levenberg - Marquardt regularization. The reconstruction algorithms such as Split Bregman and Gradient projection for sparse reconstruction (GPSR) methods are used to reconstruct the image of a human soft tissue for tumour detection. Among these algorithms, Split Bregman method provides better performance than GPSR algorithm. The parameters such as signal to noise ratio (SNR), contrast to noise ratio (CNR), relative error (RE) and CPU time for reconstructing images are analyzed to get a better performance.