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Phantoms, Imaging

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CohereNet: A Deep Learning Architecture for Ultrasound Spatial Correlation Estimation and Coherence-Based Beamforming.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Deep fully connected networks are often considered "universal approximators" that are capable of learning any function. In this article, we utilize this particular property of deep neural networks (DNNs) to estimate normalized cross correlation as a ...

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 Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convolutional ne...

Displacement Estimation in Ultrasound Elastography Using Pyramidal Convolutional Neural Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In this article, two novel deep learning methods are proposed for displacement estimation in ultrasound elastography (USE). Although convolutional neural networks (CNNs) have been very successful for displacement estimation in computer vision, they h...

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 with noise-to-noise training for denoising in SPECT myocardial perfusion imaging.

Medical physics
PURPOSE: Post-reconstruction filtering is often applied for noise suppression due to limited data counts in myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT). We study a deep learning (DL) approach for denoisi...

Mammography Image Quality Assurance Using Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: According to the European Reference Organization for Quality Assured Breast Cancer Screening and Diagnostic Services (EUREF) image quality in mammography is assessed by recording and analyzing a set of images of the CDMAM phantom. The EURE...

Multi-task convolutional neural network-based design of radio frequency pulse and the accompanying gradients for magnetic resonance imaging.

NMR in biomedicine
Modern MRI systems usually load the predesigned RFs and the accompanying gradients during clinical scans, with minimal adaption to the specific requirements of each scan. Here, we describe a neural network-based method for real-time design of excitat...

Accuracy of Touch-Based Registration During Robotic Image-Guided Partial Nephrectomy Before and After Tumor Resection in Validated Phantoms.

Journal of endourology
Image-guided surgery (IGS) allows for accurate, real-time localization of subsurface critical structures during surgery. No prior IGS systems have described a feasible method of intraoperative reregistration after manipulation of the kidney during r...

Generating anthropomorphic phantoms using fully unsupervised deformable image registration with convolutional neural networks.

Medical physics
PURPOSE: Computerized phantoms have been widely used in nuclear medicine imaging for imaging system optimization and validation. Although the existing computerized phantoms can model anatomical variations through organ and phantom scaling, they do no...