activity
20222025
collaborators

5 papers

eess.SP2025

From Narrow to Wide: Autoencoding Transformers for Ultrasound Bandwidth Recovery

Sepideh KhakzadGharamaleki, Hassan Rivaz, Brandon Helfield

Conventional pulse-echo ultrasound suffers when low-cost probes deliver only narrow fractional bandwidths, elongating pulses and erasing high-frequency detail. We address this limi…

cs.AI2024

Evaluating Detection Thresholds: The Impact of False Positives and Negatives on Super-Resolution Ultrasound Localization Microscopy

Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

Super-resolution ultrasound imaging with ultrasound localization microscopy (ULM) offers a high-resolution view of microvascular structures. Yet, ULM image quality heavily relies o…

eess.IV2024

Ensemble Learning for Microbubble Localization in Super-Resolution Ultrasound

Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

Super-resolution ultrasound (SR-US) is a powerful imaging technique for capturing microvasculature and blood flow at high spatial resolution. However, accurate microbubble (MB) loc…

eess.IV2023

Deformable-Detection Transformer for Microbubble Localization in Ultrasound Localization Microscopy

Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

To overcome the half a wavelength resolution limitations of ultrasound imaging, microbubbles (MBs) have been utilized widely in the field. Conventional MB localization methods are…

eess.IV2022

Transformer-Based Microbubble Localization

Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

Ultrasound Localization Microscopy (ULM) is an emerging technique that employs the localization of echogenic microbubbles (MBs) to finely sample and image the microcirculation beyo…