Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions
Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions
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DOI：
10.1117/1.jbo.25.8.085003
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发表时间：
2020-08-01
影响因子：
3.5
通讯作者：
Cox, Ben
中科院分区：
文献类型：
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作者：
Bench, Ciaran;Hauptmann, Andreas;Cox, Ben
意义：二维(2-D)完全卷积神经网络已被证明能够从简单组织模型的二维模拟图像中产生SO(2)的映射。然而，它们在体内产生准确估计的潜力是不确定的，因为当问题本质上是三维(3-D)时，它们受到训练数据的2-D性质的限制，目的：为了展示深度神经网络处理完整的三维图像和从真实的组织模型/图像输出血管SO(2)的三维地图的能力。方法：训练两个独立的全卷积神经网络，从组织模型的多波长模拟图像生成血管血氧饱和度和血管位置的三维地图。结果：40例真实平均血管SO(2)与网络输出的绝对差的平均值为4.4%，标准偏差为4.5%。结论：3-D完全卷积网络被证明能够使用在模拟真实成像场景的条件下生成的3D图像中所包含的全部空间信息来生成准确的SO(2)地图。我们证明，网络可以处理真实图像中存在的一些混淆效应，例如有限视角的伪影，并有可能在活体中产生准确的估计。(C)作者。
Significance: Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO(2) from 2-D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as they are limited by the 2-D nature of the training data when the problem is inherently three-dimensional (3-D), and they have not been tested with realistic images.Aim: To demonstrate the capability of deep neural networks to process whole 3-D images and output 3-D maps of vascular sO(2) from realistic tissue models/images.Approach: Two separate fully convolutional neural networks were trained to produce 3-D maps of vascular blood oxygen saturation and vessel positions from multiwavelength simulated images of tissue models.Results: The mean of the absolute difference between the true mean vessel sO(2) and the network output for 40 examples was 4.4% and the standard deviation was 4.5%.Conclusions: 3-D fully convolutional networks were shown capable of producing accurate sO(2) maps using the full extent of spatial information contained within 3-D images generated under conditions mimicking real imaging scenarios. We demonstrate that networks can cope with some of the confounding effects present in real images such as limited-view artifacts and have the potential to produce accurate estimates in vivo. (C) The Authors.