Limited View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning

by   Steven Guan, et al.

Photoacoustic tomography (PAT) is a nonionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their view of the imaging target, which result in significant image reconstruction artifacts degrading image quality. Iterative reconstruction methods can be used to reduce artifacts but are computationally expensive. In this work, we propose a novel deep learning approach termed pixelwise deep learning (PixelDL) that first employs pixelwise interpolation governed by the physics of photoacoustic wave propagation and then uses a convolution neural network to directly reconstruct an image. Simulated photoacoustic data from synthetic vasculature phantom and mouse-brain vasculature were used for training and testing, respectively. Results demonstrated that PixelDL achieved comparable performance to iterative methods and outperformed other CNN-based approaches for correcting artifacts. PixelDL is a computationally efficient approach that enables for realtime PAT rendering and for improved image quality, quantification, and interpretation.


page 4

page 5


AS-Net: Fast Photoacoustic Reconstruction with Multi-feature Fusion from Sparse Data

Photoacoustic (PA) imaging is a biomedical imaging modality capable of a...

Dense Dilated UNet: Deep Learning for 3D Photoacoustic Tomography Image Reconstruction

In photoacoustic tomography (PAT), the acoustic pressure waves produced ...

Photoacoustic Image Reconstruction Beyond Supervised to Compensate Limit-view and Remove Artifacts

Photoacoustic computed tomography (PACT) reconstructs the initial pressu...

Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging

Photoacoustic imaging (PAI) can image high-resolution structures of clin...

Deep Learning Can Reverse Photon Migration for Diffuse Optical Tomography

Can artificial intelligence (AI) learn complicated non-linear physics? H...

OT-driven Multi-Domain Unsupervised Ultrasound Image Artifact Removal using a Single CNN

Ultrasound imaging (US) often suffers from distinct image artifacts from...

A Bayesian Optimization Approach for Attenuation Correction in SPECT Brain Imaging

Photon attenuation and scatter are the two main physical factors affecti...