I have developed the first analytical and finite element model of tumors in a poroelastographic imaging
setup considering the complex mechanopathological
parameters of the tumor, i.e., elevated interstitial fluid pressure (IFP) and solid stress. I also reported the first
measurement of these parameters in vivo using an ultrasound technique.
PhD Projects:
Ultrasound poroelastography (Ultrasound and elasticity imaging Lab, Dept. of ECEN, TAMU)
5. Signal processing techniques for robust estimation of tumor mechanical parameters:
We developed methods based on priciple component analysis, Fourier theory and variable
projection to estimate the mechanical parameters of tumors robustly in noisy
elastography imaging environments.
4. Estimation of mechanopathological parameters:
We used ultrasound poroelastography to estimate the elevated IFP and solid stress distribution
inside cancerous tumors.
3. Estimation of interstitial and vascular permeabilities:
We used poroelastography to estimate the interstitial and vascular permeabilities of solid tumors.
2. Estimation of Young's modulus and Poisson's ratio:
We developed an algorithm which can estimate the Young's modulus and Poisson's ratio
of a cancer tumor irrespective of the shape of the tumor and boundary conditions.
1. Estimation of lateral strain:
Because of the limited lateral resolution of the ultrasound transducer, estimate
of the lateral strain is worse than the estimate of axial strain. We have improved
the estimate of lateral strain by more than 70% with respect to state of the art
strain estimation techniques.
Structured illumination microsocpy (Ward-Ober Lab, Dept. of BMEN, TAMU)
2. EM based image deconvolution and SIM image reconstruction:
I developed EM (expectation-maximization) based image deconvolution and structured illumination
microscopy (SIM) image reconstruction methods, which is found to be more robust to noise than
other available methods.
1. Low-cost SIM setup development:
I developed a structured illumination microscope, which cost only 4800 USD.