Research Overview
We are interested in developing advanced imaging algorithms for ultrasound-based shear wave elastography. We work toward creating efficient mathematical models for solving inverse problems in shear wave imaging to create new imaging biomarkers. We are also interested in using deep learning techniques for image reconstruction, enhancement, and segmentation.
Ultrasound shear wave elastography is a non-invasive, safe, cost-effective technique that has the potential to become a popular imaging tool for Metabolic Dysfunction-associated Steatotic Liver Disease (commonly also known as fatty liver) diagnosis. People with diabetes and obesity are at higher risk of developing fatty liver. India may have the highest fatty liver patients in the world at around 6 crores. We want to create new imaging biomarkers that can potentially be utilized in the diagnosis of several soft tissue related diseases including fatty liver, breast cancer, and DVT.
We have also worked in photoacoustic/NIR imaging for breast cancer research. It is estimated that breast cancer is the second most fatal disease among women and 1 in 8 women (in developed countries) has the risk of getting breast cancer.
Research Projects
Ultrasound Shear Wave Elastography
Focusing high-frequency ultrasound radiation in biological tissues can induce shear waves propagation (see video, credit: Marko Orescanin). The radiation force causes a few micrometers displacement within the tissue that propagates as a transient shear wave. Often the objective is to indirectly measure the viscoelasticity of the tissue by monitoring the propagation of shear waves inside it. Shear waves are known to propagate faster in stiffer media and slower in softer media. Different stiffness scores for diagnostic interpretation of pathological conditions are proposed for clinical use. Nonalcoholic steatohepatitis (NASH), which causes liver damage, is diagnosed most often in patients with obesity, dyslipidemia, and glucose intolerance. Most patients are asymptomatic, the prognosis is hard to predict, and it could lead to the risk of death from liver-related illness. Viscoelastic parameters of liver tissue can act as biomarkers of dysfunction that can be correlated to tissue pathology. Ultrasound shear wave elastography can be developed into a suitable diagnosis technique. In other diseases, such as deep vein thrombosis, the viscoelasticity of coagulating blood can be computed by solving the inverse problem of ultrasound wave propagation in clotting blood.
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Photoacoustic Image reconstruction
Photoacoustic tomography (PAT) is a noninvasive and safe imaging technique. Photoacoustic image reconstruction is an inverse problem to reconstruct initial pressure rise in the tissue and reconstruct optical properties. Model-based image reconstruction techniques yield better quantitative accuracy in photoacoustic image reconstruction. Creating new models for image reconstruction and enhancement in PAT can be immensely useful for diagnosing breast cancer. We have previously developed model-based reconstruction algorithms for PAT that improved computational efficiency and image quality.
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Light propagation in biological tissues
The attenuation of near-infrared (NIR) light intensity as it propagates in a turbid medium like biological tissue is described by modified Beer-Lambert law. The modified Beer-Lambert law (MBLL) is generally used to quantify the changes in tissue chromophore concentrations for NIR spectroscopic data analysis. Even though the MBLL is effective in terms of providing a qualitative comparison, it suffers from its applicability across tissue types and tissue dimensions. A Lambert-W function based modeling for light propagation in biological tissues, which is a generalized version of the Beer-Lambert model provides accurate and computationally faster estimations.
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