Over the past years, deep learning has established itself as a powerful tool across a broad spectrum of domains. While deep neural networks initially found nurture in the computer vision community, they have quickly spread over medical imaging applications, ranging from image analysis and interpretation to—more recently—image formation and reconstruction. Deep learning is now rapidly gaining attention in the ultrasound community, with many groups around the world exploring a wealth of opportunities to improve ultrasound imaging in several key aspects, ranging from beamforming and compressive sampling to speckle suppression, segmentation, and super-resolution imaging.

中文翻译：

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超声医学中的深度学习-从图像形成到图像分析

在过去的几年中，深度学习已经成为广泛领域中的强大工具。深度神经网络最初在计算机视觉社区中得到培育，但它们已迅速遍及医学成像应用，范围从图像分析和解释到最近的图像形成和重建。如今，深度学习在超声领域迅速得到关注，世界各地的许多团体都在从波束成形和压缩采样到斑点抑制，分割和超分辨率成像等几个关键方面探索改善超声成像的大量机会。