Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging.
Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging.
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DOI：
10.3390/s21134570
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发表时间：
2021-07-03
期刊：
影响因子：
--
通讯作者：
Guasch L
中科院分区：
文献类型：
--
作者：
Robins T;Camacho J;Agudo OC;Herraiz JL;Guasch L
超声乳腺成像是传统乳房X光检查的一种有前途的替代方法，因为它不会使妇女暴露在有害的电离辐射中，并且可以成功地对致密乳腺组织进行成像。然而，常规超声成像仅提供具有有限诊断价值的形态学信息。超声计算机断层扫描（USCT）在对乳房成像时使用透射和反射能量，以提供与诊断相关的定量组织特性，但它通常基于飞行时间断层扫描或波动方程的类似射线近似，导致重建图像分辨率低。全波形反演（FWI）基于波传播现象的更精确近似，因此可以使用低于1兆赫的频率产生非常高分辨率的图像。然而，这些低频在大多数USCT采集系统中不可用，因为它们使用中心频率远高于FWI所需频率的换能器。为了解决这个问题，我们设计、训练并实现了一个二维卷积神经网络，以人为地生成USCT数据中缺失的低频。我们的研究结果表明，FWI重建后的应用所提出的方法成功地收敛使用实验数据，表现出良好的一致性与X射线CT和反射超声断层成像图像。
Ultrasound breast imaging is a promising alternative to conventional mammography because it does not expose women to harmful ionising radiation and it can successfully image dense breast tissue. However, conventional ultrasound imaging only provides morphological information with limited diagnostic value. Ultrasound computed tomography (USCT) uses energy in both transmission and reflection when imaging the breast to provide more diagnostically relevant quantitative tissue properties, but it is often based on time-of-flight tomography or similar ray approximations of the wave equation, resulting in reconstructed images with low resolution. Full-waveform inversion (FWI) is based on a more accurate approximation of wave-propagation phenomena and can consequently produce very high resolution images using frequencies below 1 megahertz. These low frequencies, however, are not available in most USCT acquisition systems, as they use transducers with central frequencies well above those required in FWI. To circumvent this problem, we designed, trained, and implemented a two-dimensional convolutional neural network to artificially generate missing low frequencies in USCT data. Our results show that FWI reconstructions using experiment data after the application of the proposed method successfully converged, showing good agreement with X-ray CT and reflection ultrasound-tomography images.
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