기본 정보
연구 분야
프로젝트
논문
구성원
preprint|
green
·인용수 0
·2021
Improved Ultrasound Localization Microscopy based on Microbubble Uncoupling via Transmit Excitation (MUTE)
Jihun Kim, Mathew R. Lowerison, Nathiya Chandra Sekaran, Zhengchang Kou, Zhijie Dong, Michael L. Oelze, Daniel A. Llano, Pengfei Song
bioRxiv (Cold Spring Harbor Laboratory)
초록

Abstract Ultrasound localization microscopy (ULM) demonstrates great potential for visualization of tissue microvasculature at depth with high spatial resolution. The success of ULM heavily depends on the robust localization of isolated microbubbles (MBs), which can be challenging in vivo especially within larger vessels where MBs can overlap and cluster close together. While MB dilution alleviates the issue of MB overlap to a certain extent, it drastically increases the data acquisition time needed for MBs to populate the microvasculature, which is already on the order of several minutes using recommended MB concentrations. Inspired by optical super-resolution imaging based on stimulated emission depletion (STED), here we propose a novel ULM imaging sequence based on microbubble uncoupling via transmit excitation (MUTE). MUTE “silences” MB signals by creating acoustic nulls to facilitate MB separation, which leads to robust localization of MBs especially under high concentrations. The efficiency of localization accomplished via the proposed technique was first evaluated in simulation studies with conventional ULM as a benchmark. Then an in vivo study based on the chorioallantoic membrane (CAM) of chicken embryos showed that MUTE could reduce the data acquisition time by half thanks to the enhanced MB separation and localization. Finally, the performance of MUTE was validated in an in vivo mouse brain study. These results demonstrate the high MB localization efficacy of MUTE-ULM, which contributes to a reduced data acquisition time and improved temporal resolution for ULM.

키워드
MicrobubblesIn vivoComputer scienceSuperresolutionSTED microscopyBenchmark (surveying)Biomedical engineeringUltrasoundChemistryArtificial intelligence
타입
preprint
IF / 인용수
- / 0
게재 연도
2021

주식회사 디써클

대표 장재우,이윤구서울특별시 강남구 역삼로 169, 명우빌딩 2층 (TIPS타운 S2)대표 전화 0507-1312-6417이메일 info@rndcircle.io사업자등록번호 458-87-03380호스팅제공자 구글 클라우드 플랫폼(GCP)

© 2026 RnDcircle. All Rights Reserved.