High-intensity focused ultrasound thermal lesion detection using entropy imaging of ultrasound radio frequency signal time series

超声波 高强度聚焦超声 医学 治疗性超声 斑点图案 无线电频率 熵(时间箭头) 生物医学工程 放射科 计算机科学 人工智能 物理 电信 量子力学
作者
Hamid Behnam,M. Abbasi Monfared,Parisa Rangraz,Jahangir Tavakkoli
出处
期刊:Journal of Medical Ultrasound [Medknow Publications]
卷期号:26 (1): 24-24 被引量:14
标识
DOI:10.4103/jmu.jmu_3_17
摘要

During the past few decades, high-intensity focused ultrasound (HIFU) modality has been gaining surging interest in various therapeutic applications such as non- or minimally-invasive cancer treatment. Among other attributes, robust and real-time HIFU treatment monitoring and lesion detection have become essential issues for successful clinical acceptance of the modality. More recently, ultrasound radio frequency (RF) time series imaging has been studied by a number of researchers.The objective of this study is to investigate the applicability of entropy parameter of RF time series of ultrasound backscattered signals, a. k. a. Entropy imaging, toward HIFU thermal lesion detection. To this end, five fresh ex vivo porcine muscle tissue samples were exposed to HIFU exposures with total acoustic powers ranging from 30 to 110 Watts. The contrast-to-speckle ratio (CSR) values of the entropy images and their corresponding B-mode images of pre-, during- and post-HIFU exposure for each acoustic power were calculated.The novelty of this study is the use of Entropy parameter on ultrasound RF time series for the first time. Statistically significant differences were obtained between the CSR values for the B mode and entropy images at various acoustic powers. In case of 110 Watt, a CSR value 3.4 times higher than B-mode images was accomplished using the proposed method. Furthermore, the proposed method is compared with the scaling parameter of Nakagami imaging and same data which are used in this study.Entropy has the potential for using as an imaging parameter for differentiating lesions in HIFU surgery.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
pluto应助anyone采纳,获得10
3秒前
6秒前
Chen完成签到,获得积分10
6秒前
8秒前
8秒前
9秒前
小桑桑发布了新的文献求助20
9秒前
10秒前
11秒前
li_wei发布了新的文献求助30
12秒前
Ava应助名字长丶好记采纳,获得10
12秒前
13秒前
林盒发布了新的文献求助10
13秒前
空心胶囊完成签到,获得积分10
13秒前
SYLH应助xxxxxn采纳,获得10
14秒前
SYLH应助xxxxxn采纳,获得10
14秒前
共享精神应助ikun采纳,获得10
14秒前
。。。完成签到 ,获得积分10
14秒前
16秒前
tao完成签到,获得积分10
17秒前
17秒前
tt完成签到,获得积分10
17秒前
wadaxiwa应助swordlee采纳,获得10
18秒前
fyh发布了新的文献求助10
19秒前
20秒前
Crystal发布了新的文献求助10
20秒前
22秒前
刘荣圣完成签到,获得积分10
23秒前
Arvilzzz完成签到,获得积分10
23秒前
大脑袋应助tao采纳,获得30
24秒前
24秒前
wanci应助鱼咬羊采纳,获得10
24秒前
24秒前
谢紫玲发布了新的文献求助10
25秒前
桐桐应助ltt采纳,获得10
25秒前
26秒前
深海鳕鱼完成签到,获得积分10
27秒前
情怀应助Arvilzzz采纳,获得30
28秒前
ding应助mu采纳,获得10
29秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Comprehensive Computational Chemistry 1000
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3551910
求助须知:如何正确求助?哪些是违规求助? 3128345
关于积分的说明 9377313
捐赠科研通 2827348
什么是DOI,文献DOI怎么找? 1554303
邀请新用户注册赠送积分活动 725429
科研通“疑难数据库(出版商)”最低求助积分说明 714834