Three-dimensional ultrasound imaging.

This review is about the development of three-dimensional (3D) ultrasonic medical imaging, how it works, and where its future lies. It assumes knowledge of two-dimensional (2D) ultrasound, which is covered elsewhere in this issue. The three main ways in which 3D ultrasound may be acquired are described: the mechanically swept 3D probe, the 2D transducer array that can acquire intrinsically 3D data, and the freehand 3D ultrasound. This provides an appreciation of the constraints implicit in each of these approaches together with their strengths and weaknesses. Then some of the techniques that are used for processing the 3D data and the way this can lead to information of clinical value are discussed. A table is provided to show the range of clinical applications reported in the literature. Finally, the discussion relating to the technology and its clinical applications to explain why 3D ultrasound has been relatively slow to be adopted in routine clinics is drawn together and the issues that will govern its development in the future explored.

Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Shape vs. volume: Invariant shape descriptors for 3D region of interest characterization in MRI

We propose a new approach for quantifying regions of interest (ROIs) in medical image data. Rotationally invariant shape descriptors (ISDs) were applied to 3D brain regions extracted from MRI scans of 5 Parkinson's patients and 10 control subjects. We concentrated on the thalamus and the caudate nucleus since prior studies have suggested they are affected in Parkinson's disease (PD). In the caudate, both the ISD and volumetric analyses found significant differences between control and PD subjects. The ISD analysis however revealed additional differences between the left and right caudate nuclei in both control and PD subjects. In the thalamus, the volumetric analysis showed significant differences between PD and control subjects, while ISD analysis found significant differences between the left and right thalami in control subjects but not in PD patients, implying disease-induced shape changes. These results suggest that employing ISDs for ROI characterization both complements and extends traditional volumetric analyses. © 2006 IEEE.

Multidirectional scattering models for 3-dimensional ultrasound imaging

An ultrasound image is created from backscattered echoes originating from both diffuse and directional scattering. It is potentially useful to separate these two components for the purpose of tissue characterization. This article presents several models for visualization of scattering fields on 3-dimensional (3D) ultrasound imaging. By scanning the same anatomy from multiple directions, we can observe the variation of specular intensity as a function of the viewing angle. This article considers two models for estimating the diffuse and specular components of the backscattered intensity: a modification of the well-known Phong reflection model and an existing exponential model. We examine 2-dimensional implementations and also propose novel 3D extensions of these models in which the probe is not constrained to rotate within a plane. Both simulation and experimental results show that improved performance can be achieved with 3D models. © 2013 by the American Institute of Ultrasound in Medicine.

Adapting data processing to compare model and experiment accurately: A discrete element model and magnetic resonance measurements of a 3d cylindrical fluidized bed

Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. © 2013 American Chemical Society.

Novel fluid grid and voidage calculation techniques for a discrete element model of a 3D cylindrical fluidized bed

A discrete element model (DEM) combined with computational fluid dynamics (CFD) was developed to model particle and fluid behaviour in 3D cylindrical fluidized beds. Novel techniques were developed to (1) keep fluid cells, defined in cylindrical coordinates, at a constant volume in order to ensure the conditions for validity of the volume-averaged fluid equations were satisfied and (2) smoothly and accurately measure voidage in arbitrarily shaped fluid cells. The new technique for calculating voidage was more stable than traditional techniques, also examined in the paper, whilst remaining computationally-effective. The model was validated by quantitative comparison with experimental results from the magnetic resonance imaging of a fluidised bed analysed to give time-averaged particle velocities. Comparisons were also made between theoretical determinations of slug rise velocity in a tall bed. It was concluded that the DEM-CFD model is able to investigate aspects of the underlying physics of fluidisation not readily investigated by experiment. © 2014 The Authors.