Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo | Paper Citation Record

Observation b2e28b48-d6b4-4e94-8563-49cb237dead6 · outbound

This paper cites A practical guide to photoacoustic tomography in the life sciences,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo A practical guide to photoacoustic tomography in the life sciences,

Reference 1

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This paper cites Tutorial on photoacoustic tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Tutorial on photoacoustic tomography,

Reference 2

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Observation 8c827efe-6a22-4103-9e9b-9165910e66b0 · outbound

This paper cites Review of Low- Cost Photoacoustic Sensing and Imaging Based on Laser Diode and Light-Emitting Diode,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Review of Low- Cost Photoacoustic Sensing and Imaging Based on Laser Diode and Light-Emitting Diode,

Reference 3

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Observation b03f6409-7818-45eb-b34c-4e886ca2847f · outbound

This paper cites Tutorial on Photoacoustic Microscopy and Computed Tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Tutorial on Photoacoustic Microscopy and Computed Tomography,

Reference 4

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Observation 72f454db-d3da-4358-96c0-5b5fc15c1256 · outbound

This paper cites Photoacoustic tomography: in vivo imaging from organelles to organs,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Photoacoustic tomography: in vivo imaging from organelles to organs,

Reference 5

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This paper cites Photoacoustic Classification of Tumor Model Morphology Based on Support Vector Machine: A Simulation and Phantom Study,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Photoacoustic Classification of Tumor Model Morphology Based on Support Vector Machine: A Simulation and Phantom Study,

Reference 6

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Observation 5cadcb94-f7a1-427a-ab0e-016fb2bbee6e · outbound

This paper cites Single - Wavelength Blood Oxygen Saturation Sensing With Combined Optical Absorption and Scattering,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Single - Wavelength Blood Oxygen Saturation Sensing With Combined Optical Absorption and Scattering,

Reference 7

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Observation 12fca01c-3dd6-4e38-b35f-de63351015e2 · outbound

This paper cites Detection of aqueous glucose based on a cavity size - and optical -wavelength- independent continuous-wave photoacoustic technique,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Detection of aqueous glucose based on a cavity size - and optical -wavelength- independent continuous-wave photoacoustic technique,

Reference 8

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Observation 1eea36c3-3d1b-48bc-a8ed-f2e3ca9ae220 · outbound

This paper cites In vivo noninvasive monitoring of glucose concentration in human epidermis by mid-infrared pulsed photoacoustic spectroscopy,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo In vivo noninvasive monitoring of glucose concentration in human epidermis by mid-infrared pulsed photoacoustic spectroscopy,

Reference 9

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This paper cites Dual- contrast nonlinear photoacoustic sensing and imaging based on single high-repetition-rate pulsed laser,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Dual- contrast nonlinear photoacoustic sensing and imaging based on single high-repetition-rate pulsed laser,

Reference 10

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Observation d6278c55-c668-4af9-ad26-ca0c61900b20 · outbound

This paper cites Hybrid multi-wavelength nonlinear photoacoustic sensing and imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Hybrid multi-wavelength nonlinear photoacoustic sensing and imaging,

Reference 11

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Observation 6cb9deea-4913-4203-8962-c0ab0748f53b · outbound

This paper cites Single-breath-hold photoacoustic computed tomography of the breast,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Single-breath-hold photoacoustic computed tomography of the breast,

Reference 12

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.087882Z

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This paper cites Three -dimensional photoacoustic imaging system in line confocal mode for breast cancer detection,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Three -dimensional photoacoustic imaging system in line confocal mode for breast cancer detection,

Reference 13

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.075592Z

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This paper cites Single laser pulse generates dual photoacoustic signals for differential contrast photoacoustic imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Single laser pulse generates dual photoacoustic signals for differential contrast photoacoustic imaging,

Reference 14

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.060609Z

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Observation cc297a36-bbcd-465a-9938-3940b67cb5c9 · outbound

This paper cites Imaging of hemoglobin oxygen saturation variations in single vesselsin vivousing photoacoustic microscopy,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Imaging of hemoglobin oxygen saturation variations in single vesselsin vivousing photoacoustic microscopy,

Reference 15

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.046246Z

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Observation 7604864c-34b3-4210-81cc-76039d967d6b · outbound

This paper cites Image Reconstruction is a New Frontier of Machine Learning,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Image Reconstruction is a New Frontier of Machine Learning,

Reference 16

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Observation f90c6977-aba6-4e6d-8790-6eeb7b0ab544 · outbound

This paper cites Deep Convolutional Neural Network for Inverse Problems in Imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Deep Convolutional Neural Network for Inverse Problems in Imaging,

Reference 17

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Observation a4c69328-8baa-4e47-bf39-df54186e140c · outbound

This paper cites End -to-end deep neural network for optical inversion in quantitative photoacoustic imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo End -to-end deep neural network for optical inversion in quantitative photoacoustic imaging,

Reference 18

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.033187Z

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Observation 552fd498-29d8-410e-9a77-6c334d3cb8b2 · outbound

This paper cites Real-time photoacoustic projection imaging using deep learning.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Real-time photoacoustic projection imaging using deep learning

Reference 19

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Observation caaf91d1-0e5b-4719-ba2f-40be89570340 · outbound

This paper cites Reconstruction of initial pressure from limited view photoacoustic images using deep learning,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Reconstruction of initial pressure from limited view photoacoustic images using deep learning,

Reference 20

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Observation 37a4658d-c82d-41e7-8b47-2acfe5940e35 · outbound

This paper cites A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction,

Reference 21

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This paper cites A deep learning architecture for limited -angle computed tomography reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo A deep learning architecture for limited -angle computed tomography reconstruction,

Reference 22

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Observation 9f7bfc06-2a91-4024-945f-c9b08a71345a · outbound

This paper cites A U-Nets cascade for sparse view computed tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo A U-Nets cascade for sparse view computed tomography,

Reference 23

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Observation f7c0e2ba-9349-4ac0-93f9-bbec8155f81d · outbound

This paper cites CNN-Based Projected Gradient Descent for Consistent CT Image Reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo CNN-Based Projected Gradient Descent for Consistent CT Image Reconstruction,

Reference 24

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This paper cites Enabling fast and high quality LED photoacoustic imaging: a recurrent neural networks based approach,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Enabling fast and high quality LED photoacoustic imaging: a recurrent neural networks based approach,

Reference 25

Resolution: verified exact; doi, observed 2026-08-14T15:37:09.020130Z

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This paper cites Towards a Fast and Safe LED -Based Photoacoustic Imaging Using Deep Convolutional Neural Network,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Towards a Fast and Safe LED -Based Photoacoustic Imaging Using Deep Convolutional Neural Network,

Reference 26

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This paper cites MoDL: Model Based Deep Learning Architecture for Inverse Problems,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo MoDL: Model Based Deep Learning Architecture for Inverse Problems,

Reference 27

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This paper cites A Partially Learned Algorithm for Joint Photoacoustic Reconstruction and Segmentation.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo A Partially Learned Algorithm for Joint Photoacoustic Reconstruction and Segmentation

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-14T15:37:09.700716Z

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This paper cites Approximate k -space models and Deep Learning for fast photoacoustic reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Approximate k -space models and Deep Learning for fast photoacoustic reconstruction,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.370473Z

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This paper cites Model -Based Learning for Accelerated, Limited-View 3 -D Photoacoustic Tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Model -Based Learning for Accelerated, Limited-View 3 -D Photoacoustic Tomography,

Reference 30

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This paper cites Hybrid Neural Network for Photoacoustic Imaging Reconstr uction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Hybrid Neural Network for Photoacoustic Imaging Reconstr uction,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.357527Z

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Observation b8689658-8a2b-4669-8e19-e73ad8966465 · outbound

This paper cites Photoacoustic imaging in biomedicine,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Photoacoustic imaging in biomedicine,

Reference 32

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Observation 8e96a4a2-0322-4fb5-b5ab-49492f397d53 · outbound

This paper cites Universal back -projection algorithm for photoacoustic computed tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Universal back -projection algorithm for photoacoustic computed tomography,

Reference 33

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This paper cites Double Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear -Array Photoacoustic Imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Double Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear -Array Photoacoustic Imaging,

Reference 34

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This paper cites The delay multiply and sum beamforming algorithm in ultrasound B -mode medical imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo The delay multiply and sum beamforming algorithm in ultrasound B -mode medical imaging,

Reference 35

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This paper cites Photoacoustic image formation based on sparse regularization of minimum variance beamformer,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Photoacoustic image formation based on sparse regularization of minimum variance beamformer,

Reference 36

Resolution: verified exact; doi, observed 2026-08-14T15:37:08.979317Z

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Observation d5f0053c-4a21-49cb-906b-eaabb1ab381e · outbound

This paper cites Three -dimensional optoacoustic reconstruction using fast sparse representation,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Three -dimensional optoacoustic reconstruction using fast sparse representation,

Reference 37

Resolution: verified exact; doi, observed 2026-08-14T15:37:08.963972Z

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This paper cites Total variation based gradient descent algorithm for sparse -view photoacoustic image reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Total variation based gradient descent algorithm for sparse -view photoacoustic image reconstruction,

Reference 38

Resolution: verified exact; doi, observed 2026-08-14T15:37:08.949988Z

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Observation 1d81959b-71e5-4d6e-9efd-2a21dfdfa901 · outbound

This paper cites Investigation of iterative image reconstruction in three - dimensional optoacoustic tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Investigation of iterative image reconstruction in three - dimensional optoacoustic tomography,

Reference 39

Resolution: verified exact; doi, observed 2026-08-14T15:37:08.935759Z

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Observation 64eae165-f82c-4372-8f96-5aa9fe728423 · outbound

This paper cites Full-wave itera tive image reconstruction in photoacoustic tomography with acoustically inhomogeneous media,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Full-wave itera tive image reconstruction in photoacoustic tomography with acoustically inhomogeneous media,

Reference 40

Resolution: metadata mismatch; raw_fallback, observed 2026-08-14T15:37:09.469025Z

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Observation a7fe26c2-6cde-4d03-abfa-fbfe782bcedc · outbound

This paper cites Fractional Regularization to Improve Photoacoustic Tomographic Image Reconstruction,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Fractional Regularization to Improve Photoacoustic Tomographic Image Reconstruction,

Reference 41

Resolution: metadata mismatch; raw_fallback, observed 2026-08-14T15:37:09.389333Z

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Observation 973da580-4d0a-42c2-a186-d6929aa5da7d · outbound

This paper cites An algorithm for total variation regularized photoaco ustic imaging,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo An algorithm for total variation regularized photoaco ustic imaging,

Reference 42

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Observation 3ce4786e-0b1a-4371-bb66-2399bdc785f8 · outbound

This paper cites NETT regularization for compressed sensing photoacoustic tomography,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo NETT regularization for compressed sensing photoacoustic tomography,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.344085Z

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This paper cites U -net: Convolutional networks for biomedical image segmentation,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo U -net: Convolutional networks for biomedical image segmentation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.330970Z

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Observation 8fe86b6d-df17-47e5-a5bf-6cfe9d4cfbd7 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Adam: A Method for Stochastic Optimization

Reference 45

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This paper cites Automatic differentiation in pytorch,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Automatic differentiation in pytorch,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.319429Z

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Observation 654e4ffd-4557-4c07-ad4c-31f6c9dd8e5e · outbound

This paper cites k -Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo k -Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.308616Z

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This paper cites Ridge-based vessel segmentation in color images of the retina,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Ridge-based vessel segmentation in color images of the retina,

Reference 48

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This paper cites Image quality asse ssment: from error visibility to structural similarity,.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Image quality asse ssment: from error visibility to structural similarity,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:37:10.295917Z

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