Two collaborative papers co-authored by Dr. Md Ashikuzzaman were presented at the IEEE International Ultrasonics Symposium (IUS) 2025 in Utrecht, Netherlands.
The first, “Autonomous Selection of Energy-Based Ultrasound Speckle Tracking Parameters Using Deep Learning,”introduces a deep learning–based approach to autonomously optimize speckle-tracking parameters, enhancing the reproducibility and efficiency of strain elastography.
The second, “ShearMoFit: A Dual-Plane Ultrasound Shear Wave Motion Cleaning Technique,” proposes a robust framework to improve shear-wave motion tracking and elasticity estimation through adaptive dual-plane motion filtering.
Both studies stem from Dr. Ashikuzzaman’s postdoctoral research at Johns Hopkins University and reflect ongoing efforts to advance computational and AI-driven ultrasound imaging.