@misc{10481/94711,
year = {2024},
url = {https://hdl.handle.net/10481/94711},
abstract = {Accurate estimation of skin tumor tissue parameters is critical for diagnosing
and treating dermatology. However, signi cant challenges in this endeavor
are posed by the multilayered structure of the skin. The aim of this study is
to address these challenges through the use of two fractional rheological models:
Spring-pot (SP) and Kelvin-Voigt fractional derivative (KVFD) models.
These models are integrated with Torsional wave elastography (TWE) and
Probabilistic inverse problem (PIP) techniques. The goal is to improve the
estimation of skin tissue parameters in both laboratory and clinical settings.
The research will be conducted in two phases. In the  rst step, twelve bilayer
tissue mimicking phantoms are tested. These phantoms simulate the properties
of skin tissue using a specially developed TWE probe. The potential of
the SP and KVFD models to estimate skin tissue parameters will be explored
through inverse problem solving. Experimental data will be validated using
ultrafast imaging from the Verasonics Research System. Pearson correlation,
Dynamic time warping (DTW), and time-frequency plotting are used
to evaluate the correlation between these models and experimental results.
In the second phase, the methodology is applied to a group of healthy volunteers.
The aim of this phase is to understand the variability of skin tissue
properties among di erent individuals. It will also re ne the application of
the models in a realistic clinical context. This study is a contribution to the
 eld of dermatologic diagnostics by investigating the feasibility and e cacy
of the SP and KVFD models in conjunction with TWE. The aim of the
research is to improve the diagnostic process for skin tumors, with potential
implications for future developments in dermatological research and clinical
applications. The potential of the methodology in the  eld of dermatology is
highlighted by its application in a range of scenarios, from controlled laboratory
settings to real cases.},
organization = {Tesis Univ. Granada.},
publisher = {Universidad de Granada},
title = {Computational Approaches to Skin Cancer Detection using Torsion Wave Elastography
and Inverse Problem},
author = {Salameh Almashakbeh, Yousef Saleh},
}