Paper
12 September 2021 Extended depth of field photoacoustic microscopy using image fusion based on deep learning
Author Affiliations +
Abstract
Photoacoustic imaging (PAI) is an emerging and efficient imaging technology based on the discovery of the photoacoustic effect. It is a medical imaging technology used for internal imaging of human tissues. It combines the advantages of acoustic imaging and optical imaging. However, because it achieves high resolution through the intense focus of the laser beam, the resulting photoacoustic image will have a poor depth of field and less structural information. In order to solve this problem, an end-to-end general network fusion framework based on convolutional neural networks is applied to extract important image information from the input image through the convolutional layer, and then we use appropriate fusion rules for feature fusion, and finally the fusion features are processed to obtain large-volume and high-resolution photoacoustic images. Analyzing the source image and the fusion image can prove that the model embodies good generalization ability and excellent experimental results in the process of photoacoustic image fusion.
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Sihang Li, Zhuangzhuang Wang, Chenghao Gu, and Xianlin Song "Extended depth of field photoacoustic microscopy using image fusion based on deep learning", Proc. SPIE 11874, Illumination Optics VI, 118740N (12 September 2021); https://doi.org/10.1117/12.2600748
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KEYWORDS
Image fusion

3D image processing

Photoacoustic spectroscopy

3D image reconstruction

Photoacoustic microscopy

Feature extraction

Photoacoustic imaging

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