Contrast-Enhanced Ultrasound Imaging Based on Bubble Region Detection
Source abstract
Abstract
The study of ultrasound contrast agent imaging (USCAI) based on plane waves has recently attracted increasing attention. A series of USCAI techniques have been developed to improve the imaging quality. Most of the existing methods enhance the contrast-to-tissue ratio (CTR) using the time-frequency spectrum differences between the tissue and ultrasound contrast agent (UCA) region. In this paper, a new USCAI method based on bubble region detection was proposed, in which the frequency difference as well as the dissimilarity of tissue and UCA in the spatial domain was taken into account. A bubble wavelet based on the Doinikov model was firstly constructed. Bubble wavelet transformation (BWT) was then applied to strengthen the UCA region and weaken the tissue region. The bubble region was thereafter detected by using the combination of eigenvalue and eigenspace-based coherence factor (ESBCF). The phantom and rabbit in vivo experiment results suggested that our method was capable of suppressing the background interference and strengthening the information of UCA. For the phantom experiment, the imaging CTR was improved by 10.1 dB compared with plane wave imaging based on delay-and-sum (DAS) and by 4.2 dB over imaging based on BWT on average. Furthermore, for the rabbit kidney experiment, the corresponding improvements were 18.0 dB and 3.4 dB, respectively.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ultrasound and Hyperthermia Applications · Ultrasound Imaging and Elastography · Photoacoustic and Ultrasonic Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electronic Engineering, Fudan University, Shanghai 200433, China
Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai 200433, China
Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai 200030, China
Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200030, China
School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
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