Learning Super-Resolution Ultrasound Localization Microscopy from Radio-Frequency Data

Autor:	Hahne, Christopher, Chabouh, Georges, Couture, Olivier, Sznitman, Raphael
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Physics - Medical Physics
Druh dokumentu:	Working Paper
Popis:	Ultrasound Localization Microscopy (ULM) enables imaging of vascular structures in the micrometer range by accumulating contrast agent particle locations over time. Precise and efficient target localization accuracy remains an active research topic in the ULM field to further push the boundaries of this promising medical imaging technology. Existing work incorporates Delay-And-Sum (DAS) beamforming into particle localization pipelines, which ultimately determines the ULM image resolution capability. In this paper we propose to feed unprocessed Radio-Frequency (RF) data into a super-resolution network while bypassing DAS beamforming and its limitations. To facilitate this, we demonstrate label projection and inverse point transformation between B-mode and RF coordinate space as required by our approach. We assess our method against state-of-the-art techniques based on a public dataset featuring in silico and in vivo data. Results from our RF-trained network suggest that excluding DAS beamforming offers a great potential to optimize on the ULM resolution performance. Comment: IEEE International Ultrasonics Symposium (IUS), 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.04081 Zobrazit plný text záznamu View this record from Arxiv