Ultrasound Thermal Mapping Based on a Hybrid Method Combining Physical and Statistical Models

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• 作者：Ben-Ting Chen ; Jay Shieh ; Chang-Wei Huang ; Wen-Shiang Chen ; Shing-Ru Chen ; Chuin-Shan Chen
• 关键词：Temperature ; Ultrasonic imaging ; Physical model ; Statistical model
• 刊名：Ultrasound in Medicine and Biology
• 出版年：January, 2014
• 年：2014
• 卷：40
• 期：1
• 页码：115-129
• 全文大小：3009 K

文摘

Non-invasive temperature measurement of tissues deep inside the body has great potential for clinical applications, such as temperature monitoring during thermal therapy and early diagnosis of diseases. We developed a novel method for both temperature estimation and thermal mapping that uses ultrasound B-mode radiofrequency data. The proposed method is a hybrid that combines elements of physical and statistical models to achieve higher precision and resolution of temperature variations and distribution. We propose a dimensionless combined index (CI) that combines the echo shift differential and signal intensity difference with a weighting factor relative to the distance from the heat source. In聽vitro experiments verified that the combined index has a strong linear relationship with temperature variation and can be used to effectively estimate temperature with an average relative error <5%. This algorithm provides an alternative for imaging guidance-based techniques during thermal therapy and could easily be integrated into existing ultrasound systems.