English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Significance: 2D fully convolutional neural networks have been shown capableof producing maps of sO$_2$ from 2D simulated images of simple tissue models.However, their potential to produce accurate estimates in vivo is uncertain asthey are limited by the 2D nature of the training data when the problem isinherently 3D, and they have not been tested with realistic images.  Aim: To demonstrate the capability of deep neural networks to process whole3D images and output 3D maps of vascular sO$_2$ from realistic tissuemodels/images.  Approach: Two separate fully convolutional neural networks were trained toproduce 3D maps of vascular blood oxygen saturation and vessel positions frommultiwavelength simulated images of tissue models.  Results: The mean of the absolute difference between the true mean vesselsO$_2$ and the network output for 40 examples was 4.4% and the standarddeviation was 4.5%.  Conclusions: 3D fully convolutional networks were shown capable of producingaccurate sO$_2$ maps using the full extent of spatial information containedwithin 3D images generated under conditions mimicking real imaging scenarios.This work demonstrates that networks can cope with some of the confoundingeffects present in real images such as limited-view artefacts, and have thepotential to produce accurate estimates in vivo.

Towards accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in 3D