An adaptive intelligence algorithm for undersampled knee MRI reconstruction

Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present the application of adaptive intelligence to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is...

Visual Content Analysis and Linked Data for Automatic Enrichment of Architecture-Related Images

Built form dominates the urban space where most people live and work and provides a visual reflection of the local, regional and global esthetical, social, cultural, technological and economic factors and values. Street-view images and historical photo archives are therefore an invaluable source for sociological or historical study; however,...

High-permittivity pad design tool for 7T neuroimaging and 3T body imaging

Purpose: High-permittivity materials in the form of flexible “dielectric pads” have proved very useful for addressing RF inhomogeneities in high field MRI systems. Finding the optimal design of such pads is, however, a tedious task, reducing the impact of this technique. We present an easy-to-use software tool which allows researchers and...

Cross Domain Image Matching in Presence of Outliers

Cross domain image matching between image collections from different source and target domains is challenging in times of deep learning due to i) limited variation of image conditions in a training set, ii) lack of paired-image labels during training, iii) the existing of outliers that makes image matching domains not fully overlap. To this end,...

Accelerating compressed sensing in parallel imaging reconstructions using an efficient circulant preconditioner for cartesian trajectories

Purpose: Design of a preconditioner for fast and efficient parallel imaging (PI) and compressed sensing (CS) reconstructions for Cartesian trajectories. Theory: PI and CS reconstructions become time consuming when the problem size or the number of coils is large, due to the large linear system of equations that has to be solved in l<sub>1<...

A simulation study on the effect of optimized high permittivity materials on fetal imaging at 3T

PURPOSE: One of the main concerns in fetal MRI is the radiofrequency power that is absorbed both by the mother and the fetus. Passive shimming using high permittivity materials in the form of "dielectric pads" has previously been shown to increase the formula presented efficiency and homogeneity in different applications, while reducing the...

High-Permittivity Pad Design for Dielectric Shimming in Magnetic Resonance Imaging Using Projection-Based Model Reduction and a Nonlinear Optimization Scheme

Inhomogeneities in the transmit radio frequency magnetic field ( {\text{B}}-{1}^{+} ) reduce the quality of magnetic resonance (MR) images. This quality can be improved by using high-permittivity pads that tailor the {\text{B}}-{1}^{+} fields. The design of an optimal pad is application-specific and not straightforward and would therefore...

Recurrent Knowledge Distillation

Knowledge distillation compacts deep networks by letting a small student network learn from a large teacher network. The accuracy of knowledge distillation recently benefited from adding residual layers. We propose to reduce the size of the student network even further by recasting multiple residual layers in the teacher network into a single...