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Found 13 papers, 3 papers with code
Fast Sampling generative model for Ultrasound image reconstruction
Image reconstruction from radio-frequency data is pivotal in ultrafast plane wave ultrasound imaging.
Single PW takes a shortcut to compound PW in US imaging
We hypothesize that a single PW can take a shortcut to reach the diffusion trajectory of PWC, removing the need to begin with Gaussian noise.
Score-based Generative Models for Photoacoustic Image Reconstruction with Rotation Consistency Constraints
Photoacoustic tomography (PAT) is a newly emerged imaging modality which enables both high optical contrast and acoustic depth of penetration.
Cross-domain Self-supervised Framework for Photoacoustic Computed Tomography Image Reconstruction
We find that dynamically masking a high proportion of the channels, e. g., 80%, yields nontrivial self-supervisors in both image and signal domains, which decrease the multiplicity of the pseudo solution to efficiently reconstruct the image from fewer PA measurements with minimum error of the image.
Deep Learning Adapted Acceleration for Limited-view Photoacoustic Computed Tomography
To adapt fast and high-quality reconstruction of limited-view PA data, in this paper, a model-based method that combines the mathematical variational model with deep learning is proposed to speed up and regularize the unrolled procedure of reconstruction.
Compressed Sensing for Photoacoustic Computed Tomography Using an Untrained Neural Network
Our method can cooperate with other existing regularization, and further improve the quality.
Photoacoustic-monitored laser treatment for tattoo removal: a feasibility study
Skin blemishes and diseases have attracted increasing research interest in recent decades, due to their growing frequency of occurrence and the severity of related diseases.
AS-Net: Fast Photoacoustic Reconstruction with Multi-feature Fusion from Sparse Data
In this paper, we firstly propose to employ a novel signal processing method to make sparse PA raw data more suitable for the neural network, concurrently speeding up image reconstruction.
A Jointed Feature Fusion Framework for Photoacoustic Reconstruction
The cross-domain features from limited-view position-wise data and the reconstructed image are fused by a backtracked supervision.
Deep Learning Enables Robust and Precise Light Focusing on Treatment Needs
If light passes through the body tissues, focusing only on areas where treatment needs, such as tumors, will revolutionize many biomedical imaging and therapy technologies.
Deep learning for photoacoustic imaging: a survey
In this review, we performed an overview of some new developments and challenges in the application of machine learning to medical image analysis, with a special focus on deep learning in photoacoustic imaging.
Deep Learning Enabled Real-Time Photoacoustic Tomography System via Single Data Acquisition Channel
In this work, we develop a novel PACT system to provide real-time imaging, which is achieved by a 120-elements ultrasound array only using a single data acquisition (DAQ) channel.
Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo
Photoacoustic imaging (PAI) is an emerging non-invasive imaging modality combining the advantages of deep ultrasound penetration and high optical contrast.
