AIMC Topic: Photoacoustic Techniques

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High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning.

Journal of visualized experiments : JoVE
Surgical margin analysis (SMA), an essential procedure to confirm the complete excision of cancerous tissue in tumor resection surgery, requires intraoperative diagnostic tools to avoid repeated surgeries due to a positive surgical margin. Recently, ...

A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images i...

Exploring photoacoustic spectroscopy-based machine learning together with metabolomics to assess breast tumor progression in a xenograft model ex vivo.

Laboratory investigation; a journal of technical methods and pathology
In the current study, a breast tumor xenograft was established in athymic nude mice by subcutaneous injection of the MCF-7 cell line and assessed the tumor progression by photoacoustic spectroscopy combined with machine learning tools. The advancemen...

Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.

Radiology
Background Conventional radiologic modalities perform poorly in the radiated rectum and are often unable to differentiate residual cancer from treatment scarring. Purpose To report the development and initial patient study of an imaging system compri...

Deep Neural Network-Based Sinogram Super-Resolution and Bandwidth Enhancement for Limited-Data Photoacoustic Tomography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Photoacoustic tomography (PAT) is a noninvasive imaging modality combining the benefits of optical contrast at ultrasonic resolution. Analytical reconstruction algorithms for photoacoustic (PA) signals require a large number of data points for accura...

A Deep Learning Approach to Photoacoustic Wavefront Localization in Deep-Tissue Medium.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Optical photons undergo strong scattering when propagating beyond 1-mm deep inside biological tissue. Finding the origin of these diffused optical wavefronts is a challenging task. Breaking through the optical diffusion limit, photoacoustic (PA) imag...

Deep Learning-Based Spectral Unmixing for Optoacoustic Imaging of Tissue Oxygen Saturation.

IEEE transactions on medical imaging
Label free imaging of oxygenation distribution in tissues is highly desired in numerous biomedical applications, but is still elusive, in particular in sub-epidermal measurements. Eigenspectra multispectral optoacoustic tomography (eMSOT) and its Bay...

Deep learning protocol for improved photoacoustic brain imaging.

Journal of biophotonics
One of the key limitations for the clinical translation of photoacoustic imaging is penetration depth that is linked to the tissue maximum permissible exposures (MPE) recommended by the American National Standards Institute (ANSI). Here, we propose a...

A New Deep Learning Network for Mitigating Limited-view and Under-sampling Artifacts in Ring-shaped Photoacoustic Tomography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Photoacoustic tomography (PAT) is a hybrid technique for high-resolution imaging of optical absorption in tissue. Among various transducer arrays proposed for PAT, the ring-shaped transducer array is widely used in cross-sectional imaging application...

High-quality photoacoustic image reconstruction based on deep convolutional neural network: towards intra-operative photoacoustic imaging.

Biomedical physics & engineering express
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...