{"title":"Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localisation Microscopy with Large Tissue Displacements","authors":"Jipeng Yan, Shusei Kawara, Qingyuan Tan, Jingwen Zhu, Bingxue Wang, Matthieu Toulemonde, Honghai Liu, Ying Tan, Meng-Xing Tang","doi":"arxiv-2409.11391","DOIUrl":null,"url":null,"abstract":"Super-Resolution Ultrasound (SRUS) imaging through localising and tracking\nmicrobubbles, also known as Ultrasound Localisation Microscopy (ULM), has\ndemonstrated significant potential for reconstructing microvasculature and\nflows with sub-diffraction resolution in clinical diagnostics. However, imaging\norgans with large tissue movements, such as those caused by respiration,\npresents substantial challenges. Existing methods often require breath holding\nto maintain accumulation accuracy, which limits data acquisition time and ULM\nimage saturation. To improve image quality in the presence of large tissue\nmovements, this study introduces an approach integrating high-frame-rate\nultrasound with online precise robotic probe control. Tested on a\nmicrovasculature phantom with translation motions up to 20 mm, twice the\naperture size of the matrix array used, our method achieved real-time tracking\nof the moving phantom and imaging volume rate at 85 Hz, keeping majority of the\ntarget volume in the imaging field of view. ULM images of the moving cross\nchannels in the phantom were successfully reconstructed in post-processing,\ndemonstrating the feasibility of super-resolution imaging under large tissue\nmotions. This represents a significant step towards ULM imaging of organs with\nlarge motion.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"40 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Super-Resolution Ultrasound (SRUS) imaging through localising and tracking
microbubbles, also known as Ultrasound Localisation Microscopy (ULM), has
demonstrated significant potential for reconstructing microvasculature and
flows with sub-diffraction resolution in clinical diagnostics. However, imaging
organs with large tissue movements, such as those caused by respiration,
presents substantial challenges. Existing methods often require breath holding
to maintain accumulation accuracy, which limits data acquisition time and ULM
image saturation. To improve image quality in the presence of large tissue
movements, this study introduces an approach integrating high-frame-rate
ultrasound with online precise robotic probe control. Tested on a
microvasculature phantom with translation motions up to 20 mm, twice the
aperture size of the matrix array used, our method achieved real-time tracking
of the moving phantom and imaging volume rate at 85 Hz, keeping majority of the
target volume in the imaging field of view. ULM images of the moving cross
channels in the phantom were successfully reconstructed in post-processing,
demonstrating the feasibility of super-resolution imaging under large tissue
motions. This represents a significant step towards ULM imaging of organs with
large motion.