A feasibility study of a rotary planar electrode array for electrical impedance mammography using a digital breast phantom.

A feasibility study of an electrical impedance mammography (EIM) system with a rotary planar electrode array, named RPEIM, is presented. The RPEIM system is an evolution of the Sussex MK4 system, which is a prototype instrument for breast cancer detection. Comparing it with the other planar electrode EIM systems, the rotation feature enables a dramatic increase in the number of independent measurements. To assist impedance evaluation exploiting electrode array rotation, a synchronous mesh method is proposed. Using the synchronous mesh method, the RPEIM system is shown to have superior performance in image accuracy, spatial resolution and noise tolerance over the MK4 system. To validate the study, we report simulations based on a close-to-realistic 3D digital breast phantom, which comprises of: skin, nipple, ducts, acinus, fat and tumor. A digital breast phantom of a real patient is constructed, whose tumor was detected using the MK4 system. The reconstructed conductivity image of the breast phantom indicates that the breast phantom is a close replica of the patient's real breast as assessed by the MK4 system in a clinical trial. A comparison between the RPEIM system and the MK4 system is made based on this phantom to assess the advantages of the RPEIM system.

Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations.

The anatomy and motion of the heart and the aorta are essential for patient-specific simulations of cardiac electrophysiology, wall mechanics and hemodynamics. Within the European integrated project euHeart, algorithms have been developed that allow to efficiently generate patient-specific anatomical models from medical images from multiple imaging modalities. These models, for instance, account for myocardial deformation, cardiac wall motion, and patient-specific tissue information like myocardial scar location. Furthermore, integration of algorithms for anatomy extraction and physiological simulations has been brought forward. Physiological simulations are linked closer to anatomical models by encoding tissue properties, like the muscle fibers, into segmentation meshes. Biophysical constraints are also utilized in combination with image analysis to assess tissue properties. Both examples show directions of how physiological simulations could provide new challenges and stimuli for image analysis research in the future.

Automated tracking of migrating cells in phase-contrast video microscopy sequences using image registration.

Analysis of in vitro cell motility is a useful tool for assessing cellular response to a range of factors. However, the majority of cell-tracking systems available are designed primarily for use with fluorescently labelled images. In this paper, five commonly used tracking systems are examined for their performance compared with the use of a novel in-house cell-tracking system based on the principles of image registration and optical flow. Image registration is a tool commonly used in medical imaging to correct for the effects of patient motion during imaging procedures and works well on low-contrast images, such as those found in bright-field and phase-contrast microscopy. The five cell-tracking systems examined were Retrac, a manual tracking system used as the gold standard; CellTrack, a recently released freely downloadable software system that uses a combination of tracking methods; ImageJ, which is a freely available piece of software with a plug-in for automated tracking (MTrack2) and Imaris and Volocity, both commercially available automated tracking systems. All systems were used to track migration of human epithelial cells over ten frames of a phase-contrast time-lapse microscopy sequence. This showed that the in-house image-registration system was the most effective of those tested when tracking non-dividing epithelial cells in low-contrast images, with a successful tracking rate of 95%. The performance of the tracking systems was also evaluated by tracking fluorescently labelled epithelial cells imaged with both phase-contrast and confocal microscopy techniques. The results showed that using fluorescence microscopy instead of phase contrast does improve the tracking efficiency for each of the tested systems. For the in-house software, this improvement was relatively small (<5% difference in tracking success rate), whereas much greater improvements in performance were seen when using fluorescence microscopy with Volocity and ImageJ.

Evaluating an optical-flow-based registration algorithm for contrast-enhanced magnetic resonance imaging of the breast.

Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.

Efficient computational fluid dynamics mesh generation by image registration.

Most implementations of computational fluid dynamics (CFD) solutions require a discretisation or meshing of the solution domain. The production from a medical image of a computationally efficient mesh representing the structures of interest can be time consuming and labour-intensive, and remains a major bottleneck in the clinical application of CFD. This paper presents a method for deriving a patient-specific mesh from a medical image. The method uses volumetric registration of a pseudo-image, produced from an idealised template mesh, with the medical image. The registration algorithm used is robust and computationally efficient. The accuracy of the new algorithm is measured in terms of the distance between a registered surface and a known surface, for image data derived from casts of the lumen of two different vessels. The true surface is identified by laser profiling. The average distance between the surface points measured by the laser profiler and the surface of the mapped mesh is better than 0.2 mm. For the images analysed, the new algorithm is shown to be 2-3 times more accurate than a standard published algorithm based on maximising normalised mutual information. Computation times are approximately 18 times faster for the new algorithm than the standard algorithm. Examples of the use of the algorithm on two clinical examples are also given. The registration methodology lends itself immediately to the construction of dynamic mesh models in which vessel wall motion is obtained directly using registration.

Characterisation of the haemodynamics of the superior mesenteric artery.

In contrast to its prevalence in the surrounding vasculature, occurrence of primary atherosclerotic disease in the superior mesenteric artery (SMA) is rare (Glagov et al., 1988. Hemodynamics and atherosclerosis, Insights and perspectives gained from studies of human arteries. Archives of Pathology and Laboratory Medicine 112(10), 1018-1031; Hansen et al., 2004. Mesenteric artery disease in the elderly. Journal of Vascular Surgery 40(1), 45-52). We hypothesise that this sparing might be attributed to more favourable haemodynamic characteristics in the SMA than in other vessels locally. Dynamic magnetic resonance imaging (MRI) images established that the SMA is highly mobile (Jeays, 2006. Investigation of blood flow in the superior mesenteric artery and its potential influence on atheroma and gut ischaemia. Ph.D. Thesis, University of Sheffield), and thus that an analysis based on rigid geometry might be inappropriate. This paper describes an efficient methodology for the construction of a patient-specific, time-dependent model of an arterial segment and reports the results of a haemodynamic characterisation of the SMA for one individual. A transient computational fluid dynamic (CFD) model was constructed by morphing a parametric mesh constructed from simple geometric primitives. This process has the merit that it is easy to control the element size distribution mapped onto the original geometric primitives. It is robust in operation, and is ideally suited to the generation of dynamic CFD meshes of arterial systems that are free from major pathology. Flow boundary conditions were determined based on phase contrast MRI velocity measurements. Comparative studies with rigid walls and with moving walls, based on the transient data, indicated that, despite the significant motion of the SMA (radial dilation of the order of 10% and translation of the order of the radius), the maximum (spatially and temporally-resolved) wall shear stresses changed by no more than 21.6% of a global norm, and the average change was less than 2.1%.

Automatic segmentation of medical images using image registration: diagnostic and simulation applications.

Automatic identification of the boundaries of significant structure (segmentation) within a medical image is an are of ongoing research. Various approaches have been proposed but only two methods have achieved widespread use: manual delineation of boundaries and segmentation using intensity values. In this paper we describe an approach based on image registration. A reference image is prepared and segmented, by hand or otherwise. A patient image is registered to the reference image and the mapping then applied to ther reference segmentation to map it back to the patient image. In general a high-resolution nonlinear mapping is required to achieve accurate segmentation. This paper describes an algorithm that can efficiently generate such mappings, and outlines the uses of this tool in two relevant applications. An important feature of the approach described in this paper is that the algorithm is independent of the segmentation problem being addresses. All knowledge about the problem at hand is contained in files of reference data. A secondary benefit is that the continuous three-dimensional mapping generated is well suited to the generation of patient-specific numerical models (e.g. finite element meshes) from the library models. Smoothness constraints in the morphing algorithm tend to maintain the geometric quality of the reference mesh.

Towards magnetic detection electrical impedance tomography: data acquisition and image reconstruction of current density in phantoms and in vivo.

The objective of magnetic detection electrical impedance tomography (MD-EIT) is to reconstruct in vivo images of conductivity from magnetic field measurements taken around the body. MD-EIT is performed by applying an alternating current, at one of a range of frequencies, to a conducting object through a pair of electrodes fixed to the surface of the object. Magnetic field measurements recorded by search coils at a number of positions around the object are used to determine the current distribution that is generating the magnetic field. From this distribution, a conductivity map of a cross-section of the object can be reconstructed. This paper describes the development of an MD-EIT data acquisition system and discusses the related image reconstruction issues. The ill-conditioned nature of the inverse problem is examined and a number of image reconstruction methods are compared. The technical feasibility of MD-EIT data collection and image reconstruction is demonstrated with example images of current density from both phantom and human data.

A method of generalized projections (MGP) ghost correction algorithm for interleaved EPI.

Investigations into the method of generalized projections (MGP) as a ghost correction method for interleaved EPI are described. The technique is image-based and does not require additional reference scans. The algorithm was found to be more effective if a priori knowledge was incorporated to reduce the degrees of freedom, by modeling the ghosting as arising from a small number of phase offsets. In simulations with phase variation between consecutive shots for n-interleaved echo planar imaging (EPI), ghost reduction was achieved for n = 2 only. With no phase variation between shots, ghost reduction was obtained with n up to 16. Incorporating a relaxation parameter was found to improve convergence. Dependence of convergence on the region of support was also investigated. A fully automatic version of the method was developed, using results from the simulations. When tested on in vivo 2-, 16-, and 32-interleaved spin-echo EPI data, the method achieved deghosting and image restoration close to that obtained by both reference scan and odd/even filter correction, although some residual artifacts remained.

Image-based EPI ghost correction using an algorithm based on projection onto convex sets (POCS).

This work describes the use of a method, based on the projection onto convex sets (POCS) algorithm, for reduction of the N/2 ghost in echo-planar imaging (EPI). In this method, ghosts outside the parent image are set to zero and a model k-space is obtained from the Fourier transform (FT) of the resulting image. The zeroth- and first-order phase corrections for each line of the original k-space are estimated by comparison with the corresponding line in the model k-space. To overcome problems of phase wrapping, the first-order phase corrections for the lines of the original k-space are estimated by registration with the corresponding lines in the model k-space. It is shown that applying these corrections will result in a reduction of the ghost, and that iterating the process will result in a convergence towards an image in which the ghost is minimized. The method is tested on spin-echo EPI data. The results show that the method is robust and remarkably effective, reducing the N/2 ghost to a level nearly comparable to that achieved with reference scans.

Automatic image registration of diagnostic and radiotherapy treatment planning CT head images.

PURPOSE: Accurate image registration is an essential step to integrate information from diagnostic and radiotherapy treatment planning (RTP) CT images. In this paper a fully automatic algorithm is presented to quickly register such diagnostic and RTP CT head scans. METHODS AND MATERIALS: The registration algorithm, which regards one image as the moved version of the other, was applied to seven clinically obtained diagnostic and RTP CT data set pairs. During the RTP scan patients were in treatment position and wearing mold masks. Hence, patient position differed strongly in both image sets. Registrations were inspected visually and compared with results obtained minimizing the sum-of-square difference. RESULTS: Registrations were accurate upon visual inspection. Differences between the two algorithms were at subvoxel level. All cases were successfully registered, using several different starting points. Registration calculations took 1-2 minutes. Minimization of the sum-of-square difference took 1-1.5 hours. CONCLUSIONS: The results show that a fast and accurate image registration is achieved without prior segmentation or feature extraction and that the algorithm is robust, which makes it clinically applicable.

Incorporating a priori anatomical information into image reconstruction in electrical impedance tomography.

Image reconstruction in electrical impedance tomography using the sensitivity theorem is generally based on the assumption that the initial conductivity distribution of the body being imaged is uniform. The technique of image reconstruction using this method is described and reconstructed images are presented. Improvements in image quality and accuracy are demonstrated when accurate a priori 'anatomical' information, in the form of a model of the distribution of conductivity within the region to be imaged, is used to construct the sensitivity matrix. In practice correct a priori information is not available, for example the conductivity values within the various anatomical regions will not be known. An iterative algorithm is presented which allows the conductivity parameters of the a priori model to be determined during reconstruction.

Magnetic impedance tomography.

Tissue can be characterized by its electrical impedance, especially if measurement can be extended over a range of frequencies. Recently, there has been a great deal of interest in imaging the distribution of electrical impedance through the technique of electrical impedance tomography (EIT). However, EIT has a number of practical problems relating to the placement of electrodes on the body. Such contacts are not required to collect magnetic field data around an object through which current is flowing and thus this approach may be more practical than EIT in the clinical environment. This paper describes the technique of magnetic impedance tomography (MIT), which allows reconstruction of the current distribution from magnetic field measurements. The reconstruction techniques used to generate the images and the prototype data collection system are described. Images produced using data collected from discrete and distributed current phantoms and the thorax during human respiration are presented.

The use of image registration in the analysis of bone scans for the assessment of temporomandibular joint uptake.

Bone scanning is a commonly used technique in the assessment of patients with facial asymmetry. Uptake in the temporomandibular joints can be assessed quantitatively, either as a right-to-left ratio or as the uptake in the joint relative to some other bony structure. We used image registration techniques in the development of an automatic method of quantitative analysis and compared this with a manual region of interest method. Both image warping and region warping were studied. Normal ranges were established in a series of 25 subjects with no evidence of temporomandibular disorder. The results of this study indicate that, by using image registration and standard regions of interest, the results from normal subjects show a smaller standard deviation and improved correlation between observers when compared with manual analysis.

Efficient nonlinear registration of 3D images using high order co-ordinate transfer functions.

There is an increasing interest in image registration for a variety of medical imaging applications. Image registration is achieved through the use of a co-ordinate transfer function (CTF) which maps voxels in one image to voxels in the other image, including in the general case changes in mapped voxel intensity. If images of the same subject are to be registered the co-ordinate transfer function needs to implement a spatial transformation consisting of a displacement and a rigid rotation. In order to achieve registration a common approach is to choose a suitable quality-of-registration measure and devise a method for the efficient generation of the parameters of the CTF which minimize this measure. For registration of images from different subjects more complex transforms are required. In general function minimization is too slow to allow the use of CTFs with more than a small number of parameters. However, provided the images are from the same modality and the CTF can be expanded in terms of an appropriate set of basis functions this paper will show how relatively complex CTFs can be used for registration. The use of increasingly complex CTFs to minimize the within group standard deviation of a set of normal single photon emission tomography brain images is used to demonstrate the improved registration of images from different subjects using CTFs of increasing complexity.

Use of forward projection to correct patient motion during SPECT imaging.

We have developed an iterative method to correct axial and tangential patient motion occurring during tomographic acquisition. The method uses axial images reconstructed from the uncorrected projection images, which are then forward projected to form a basis for registering the original planar images and, in the process, directly seeks to establish a consistent data set. Our method can be applied to all SPECT scans including myocardial and brain SPECT. We demonstrate that the method is capable of detecting and quantitatively correcting for complex motion in both axial and tangential directions. Results from phantom experiments show excellent resolution and contrast recovery after simulated movement in both the axial and tangential directions and initial results with clinical data sets are encouraging.

Automatic motion correction in dynamic radionuclide renography using image registration.

Time-activity curves from dynamic renograms can be analysed to yield important quantitative parameters. However, accurate results are dependent on curves being free from artefacts caused by patient movement. We describe a method to correct for both translational and rotational motion during renography. The method is image-based and does not require markers. Sequential dynamic frames are registered using an affine transform from which rotational and translational components are extracted by singular-value decomposition. Computer simulations demonstrate correction to < 1 pixel and < 1 degree. The method is also fast, with renograms comprising 75 frames of 64 x 64 pixels taking under 1 min for correction on a Sun SPARC 5.

Three-dimensional image reconstruction for electrical impedance tomography.

Very little work has been conducted on three-dimensional aspects of electrical impedance tomography (EIT), partly due to the increased computational complexity over the two-dimensional aspects of EIT. Nevertheless, extending EIT to three-dimensional data acquisition and image reconstruction may afford significant advantages such as an increase in the size of the independent data set and improved spatial resolution. However, considerable challenges are associated with the software aspects of three-dimensional EIT systems due to the requirement for accurate three-dimensional forward problem modelling and the derivation of three-dimensional image reconstruction algorithms. This paper outlines the work performed to date to derive a three-dimensional image reconstruction algorithm for EIT based on the inversion of the sensitivity matrix approach for a finite right circular cylinder. A comparison in terms of the singular-value spectra and the singular vectors between the sensitivity matrices for a three-dimensional cylinder and a two-dimensional disc has been performed. This comparison shows that the three-dimensional image reconstruction algorithm recruits more central information at lower condition numbers than the two-dimensional image reconstruction algorithm.

Three-dimensional electrical impedance tomography.

The electrical resistivity of mammalian tissues varies widely and is correlated with physiological function. Electrical impedance tomography (EIT) can be used to probe such variations in vivo, and offers a non-invasive means of imaging the internal conductivity distribution of the human body. But the computational complexity of EIT has severe practical limitations, and previous work has been restricted to considering image reconstruction as an essentially two-dimensional problem. This simplification can limit significantly the imaging capabilities of EIT, as the electric currents used to determine the conductivity variations will not in general be confined to a two-dimensional plane. A few studies have attempted three-dimensional EIT image reconstruction, but have not yet succeeded in generating images of a quality suitable for clinical applications. Here we report the development of a three-dimensional EIT system with greatly improved imaging capabilities, which combines our 64-electrode data-collection apparatus with customized matrix inversion techniques. Our results demonstrate the practical potential of EIT for clinical applications, such as lung or brain imaging and diagnostic screening.