headshot of Zahra Hosseini

Zahra Hosseini

Researcher Graduate Student
Linkedin Google Scholar ResearchGate Bioengineering Department

overview

Ms. Zahra Hosseini is a Ph.D. candidate in Bioengineering at the University of Pittsburgh, specializing in advanced ultrasound imaging for medical diagnostics. Under the mentorship of Dr. Kang Kim, her research focuses on developing and refining super-resolution ultrasound imaging technologies to enable precise assessment of microvascular changes. Her work aims to transform noninvasive diagnostics and improve early detection for conditions associated with microvascular abnormalities.
Her research involves acquiring and analyzing ultrasound data from rabbit and mouse models to deepen the understanding of disease-related microvascular alterations. Specifically, she investigates atherosclerotic plaques induced in the femoral artery of rabbits to identify rupture-prone plaques, a major cause of strokes and acute coronary syndromes. Additionally, she assesses renal microvascular changes associated with sickle cell disease and evaluates microvascular rarefaction in sickle cell mouse models of chronic kidney disease.
Beyond data acquisition, Ms. Hosseini is dedicated to optimizing imaging techniques, conducting advanced data analysis, and validating super-resolution ultrasound (SRU) imaging against histological standards such as H&E and CD31 staining.
Ms. Hosseini earned her M.S. in Biomedical Engineering from K. N. Toosi University of Technology in 2021, where she developed an adaptive method to enhance ultrasound elastogram reconstruction. Prior to that, she earned a B.S. in Biomedical Engineering from Qazvin Islamic Azad University in 2018, where she developed novel de-speckling methods to reduce noise while preserving fine details in ultrasound images.

about

PhD, University of Pittsburgh, 2023 - present

MSc, K.N.Toosi University of Technology, 2018 - 2021

BSc, Qazvin Islamic Azad University, 2014 - 2018

Hosseini, Z., Chen, Q., Richards, T., Smith, M., Phillippi, J., Watson, A., & Kim, K. (2024). Super-Resolution Ultrasound Imaging for Assessing Vasa Vasorum in Rabbit Atherosclerotic Plaques. Washington D.C., United States.

Hosseini, Z., Khadem, A., & Bibalan, M.H. (2024). A novel stretching factor estimator based on an adaptive bisection method for ultrasound strain imaging. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 92, 106083.Elsevier. doi: 10.1016/j.bspc.2024.106083.

Hosseini, Z., Hassannejad Bibalan, M.Hosseini, Z. Entropy Based Parameter Estimation of 2D Gaussian Filter for Image Speckle Noise Removal. AUT Journal of Electrical Engineering, 53, 189-200.Amirkabir University of Technology. doi: 10.22060/eej.2021.19374.5389.

Hosseini, Z., Chen, Q., Tan, R., Ghosh, S., & Kim, K. (2024). Quantitative Assessment of Microvascular Changes Using Super-Resolution Ultrasound Imaging During Chronic Kidney Disease in Sickle Cell Mice. Poster session presented at the meeting of Bioengineering (BioE) Day.University of Pittsburgh, Pittsburgh, United States.

Hosseini, Z., Khadem, A., & Bibalan, M.H. (2022). Displacement Estimation for Ultrasound Elastography Based on a Robust Uniform Stretching Method. In 2022 30th International Conference on Electrical Engineering (ICEE), 00, (pp. 791-795).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icee55646.2022.9827135.

Hosseini, Z., Khadem, A., & Bibalan, M.H. (2021). Window-Based Strain Estimation Using Weighted Displacement Obtained From Normalized Cross-Correlation. In 2021 5th International Conference on Pattern Recognition and Image Analysis (IPRIA), 00, (pp. 1-6).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ipria53572.2021.9483489.

Hosseini, Z., & Bibalan, M.H. (2018). B-mode Ultrasonic Images Quality Enhancement Using an Intelligent 5*5 Pixels Window Averaging. In 2018 8th Conference of AI & Robotics and 10th RoboCup Iranopen International Symposium (IRANOPEN), (pp. 81-87).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/rios.2018.8406635.

Hosseini, Z., & Bibalan, M.H. (2018). Speckle Noise Reduction Of Ultrasound Images Based On Neighbor Pixels Averaging. In 2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME), 00, (pp. 1-6).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icbme.2018.8703576.