Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions.
Journal:
Journal of biomedical optics
Published Date:
Aug 1, 2020
Abstract
SIGNIFICANCE: Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO2 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.