Dimensionality reduced plug and play priors for improving photoacoustic tomographic imaging with limited noisy data

Bandwidth Improvement in Ultrasound Image Reconstruction Using Deep Learning Techniques

Ultrasound (US) imaging is a medical imaging modality that uses the reflection of sound in the range of 2-18 MHz to image internal body structures. In US, the frequency bandwidth (BW) is directly associated with image resolution. BW is a property of the transducer and more bandwidth comes at a higher cost. Thus, methods that can transform strongly bandlimited ultrasound data into broadband data are essential. In this work, we propose a deep learning (DL) technique to improve the image quality for a given bandwidth by learning features provided by broadband data of the same field of view. Therefore, the performance of several DL architectures and conventional state-of-the-art techniques for image quality improvement and artifact removal have been compared on in vitro US datasets. Two training losses have been utilized on three different architectures: a super resolution convolutional neural network (SRCNN), U-Net, and a residual encoder decoder network (REDNet) architecture. The models have been trained to transform low-bandwidth image reconstructions to high-bandwidth image reconstructions, to reduce the artifacts, and make the reconstructions visually more attractive. Experiments were performed for 20%, 40%, and 60% fractional bandwidth on the original images and showed that the improvements obtained are as high as 45.5% in RMSE, and 3.85 dB in PSNR, in datasets with a 20% bandwidth limitation.

Looking deep inside tissue with photoacoustic molecular probes: a review

Significance

Deep tissue noninvasive high-resolution imaging with light is challenging due to the high degree of light absorption and scattering in biological tissue. Photoacoustic imaging (PAI) can overcome some of the challenges of pure optical or ultrasound imaging to provide high-resolution deep tissue imaging. However, label-free PAI signals from light absorbing chromophores within the tissue are nonspecific. The use of exogeneous contrast agents (probes) not only enhances the imaging contrast (and imaging depth) but also increases the specificity of PAI by binding only to targeted molecules and often providing signals distinct from the background.

Aim

We aim to review the current development and future progression of photoacoustic molecular probes/contrast agents.

Approach

First, PAI and the need for using contrast agents are briefly introduced. Then, the recent development of contrast agents in terms of materials used to construct them is discussed. Then, various probes are discussed based on targeting mechanisms, in vivo molecular imaging applications, multimodal uses, and use in theranostic applications.

Results

Material combinations are being used to develop highly specific contrast agents. In addition to passive accumulation, probes utilizing activation mechanisms show promise for greater controllability. Several probes also enable concurrent multimodal use with fluorescence, ultrasound, Raman, magnetic resonance imaging, and computed tomography. Finally, targeted probes are also shown to aid localized and molecularly specific photo-induced therapy.

Conclusions

The development of contrast agents provides a promising prospect for increased contrast, higher imaging depth, and molecularly specific information. Of note are agents that allow for controlled activation, explore other optical windows, and enable multimodal use to overcome some of the shortcomings of label-free PAI.

Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: introduction to the feature issue

This feature issue of Biomedical Optics Express covered all aspects of translational photoacoustic research. Application areas include screening and diagnosis of diseases, imaging of disease progression and therapeutic response, and image-guided treatment, such as surgery, drug delivery, and photothermal/photodynamic therapy. The feature issue also covers relevant developments in photoacoustic instrumentation, contrast agents, image processing and reconstruction algorithms.