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Welcome and Introduction to SPIE Medical Imaging conference 11602: Ultrasonic Imaging and Tomography

Breast cancer is the most common cancer type among women. Approximately 40,000 women are expected to die from breast cancer every year. While digital mammography has a central role in the early diagnosis of breast cancer, many cancers are not visible in mammography, for example in women with dense breast tissue. Contrast enhanced magnetic resonance imaging (CE-MRI) of the breast is often used to detect lesions not visible in mammography. Lesions with suspicious characteristics on CE-MRI need to be further assessed with MRI-guided biopsy. However, MRI-guided biopsy is expensive, time consuming, and not widely available. In this paper, a novel method for a matching tool between MRI and spot mammograms is proposed. Our aim is to transfer information that is only visible in MRI onto mammographic spot projections, to enable X-ray guided biopsy even if the lesion is only visible in MRI. Two methods of registration in combination are used; a biomechanical model based registration between MRI and full view X-ray mammograms and a subsequent image based registration between full mammograms and spot mammograms. Preliminary results assessed for one patient from the Medical University of Vienna are presented. The target registration error (TRE) of biomechanical model based registration is 2.4 mm and the TRE of the image based registration is 9.5 mm. The total TRE of the two steps is 7.3 mm.

Ultrasound computer tomography (USCT) is a promising modality for breast cancer diagnosis which images the reflectivity, sound speed and attenuation of tissue. Elastic properties of breast tissue, however, cannot directly be imaged although they have shown to be applicable as a discriminator between different tissue types. In this work we propose a novel approach combining USCT with the principles of strain elastography. Socalled USCT-SE makes use of imaging the breast in two deformation states, estimating the deformation field based on reconstructed images and thereby allows localizing and distinguishing soft and hard masses. We use a biomechanical model of the breast to realistically simulate both deformation states of the breast. The analysis of the strain is performed by estimating the deformation field from the deformed to the undeformed image by a non-rigid registration. In two experiments the non-rigid registration is applied to ground truth sound speed images and simulated SAFT images. Results of the strain analysis show that for both cases soft and hard lesions can be distinguished visually in the elastograms. This paper provides a first approach to obtain mechanical information based on external mechanical excitation of breast tissue in a USCT system.

Ultrasound transmission tomography is a promising modality for breast cancer diagnosis. For image reconstruc- tion approximations to the acoustic wave equation such as straight or bent rays are commonly used due to their low computational complexity. For sparse apertures the coverage of the volume by rays is very limited, thereby requiring strong regularization in the inversion process. The concept of fat rays reduces the sparseness and includes the contributions to the measured signal originating from the first Fresnel zone. In this work we investi- gate the application of the fat ray concept to ultrasound transmission tomography. We implement a straight ray, bent ray and fat ray forward model. For the inversion process a least squares solver (LSQR), a simultaneous al- gebraic reconstruction technique (SART) and a compressive sensing based total variation minimization (TVAL3) is applied. The combination of forward models and inversion processes has been evaluated by synthetic data. TVAL3 outperforms SART and LSQR, especially for sparse apertures. The fat ray concept is able to decrease the error with respect to the ground truth compared to the bent ray method especially for SART and LSQR inversion, and especially for very sparse apertures.

Increasing interest in multimodal breast cancer diagnosis has led to the development of methods for MRI to X-ray mammography registration to provide direct correlation of modalities. The severe breast deformation in X-ray mammography is often tackled by biomechanical models, which however have not yet brought the registration accuracy to a clinically applicable level. We present a novel registration approach of MRI to X-ray tomosynthesis. Tomosynthesis provides three-dimensional information of the compressed breast and as such has the ability to open new possibilities in the registration of MRI and X-ray data. By bundling the 3D information from the tomosynthesis volume with the 2D projection images acquired at different measuring angles, we provide a correlation between the registration error in 3D and 2D and evaluate different 3D- and 2D-based similarity metrics to drive the optimization of the automated patient-specific registration approach. From the preliminary study of four analysed patients we found that the projected registration error is in general larger than the 3D error in case of small registration errors in the cranio-caudal direction. Although both image shape and intensitybased 2D similarity metrics showed a clear correlation with the 2D registration error at different projection angles, metrics that relied on the combined 2D and 3D information yielded in most of the cases the minimal registration error and as such had better performance than similarity metrics that rely only on the shape similarity of volumes.

In Ultrasound computer tomography (USCT) Synthetic aperture focusing technique (SAFT) is often applied for reflectivity image reconstruction. Phase aberration correction is essential to cope with the large sound speed differences in water and the different human tissues. In this paper we compare two approaches for phase aberration correction: a straight ray approximation using the Bresenham algorithm (B-SAFT) and a bent ray approximating using a multi-stencil Fast Marching Method (FMM-SAFT). The analysis is carried out with simulated point scatterers and simulated phantoms to measure the effect on the image resolution and contrast. The method is additionally applied to experimental data. B-SAFT degrades the image resolution and contrast in cases of large sound speed differences of objects and if the reconstructed point is close to a boundary where a change in impedance is present. FMM-SAFT is able to recover the image quality in these cases if the sound speed distribution is known accurately and with high resolution. If these requirements cannot be met, B-SAFT proved to be more robust.

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Synthetic Aperture Focusing Technique (SAFT) allows fast data acquisition and optimally focused images. The computational burden for 3D imaging is large as for each voxel the delay for each acquired A-scan has to be calculated, e.g. O(N5) for N3 voxels and N2 A-scans. For 3D reconstruction of objects which are large in terms of the wavelength, e.g. ≥ (100 λ)3, the computation of one volume takes several days on a current multicore PC. If the 3D distribution of the speed of sound is applied to correct the delays, the computation time increases further. In this work a time of flight interpolation based GPU implementation (TOFI-SAFT) is presented which accelerates our previous GPU implementation of speed of sound corrected SAFT by a factor of 7 to 16 min. with only minor reduction of image quality.

In our first clinical study with a full 3D Ultrasound Computer Tomography (USCT) system patient data was acquired in eight minutes for one breast. In this paper the patient movement during the acquisition was analyzed quantitatively and as far as possible corrected in the resulting images. The movement was tracked in ten successive reflectivity reconstructions of full breast volumes acquired during 10 s intervals at different aperture positions, which were separated by 41 s intervals. The mean distance between initial and final position was 2.2 mm (standard deviation (STD) ± 0.9 mm, max. 4.1 mm, min. 0.8 mm) and the average sum of all moved distances was 4.9 mm (STD ± 1.9 mm, max. 8.8 mm, min. 2.7 mm). The tracked movement was corrected by summing successive images, which were transformed according to the detected movement. The contrast of these images increased and additional image content became visible.

Ultrasound Computer Tomography (USCT) is a promising new imaging method for breast cancer diagnosis. We developed a 3D USCT system and tested it in a pilot study with encouraging results: 3D USCT was able to depict two carcinomas, which were present in contrast enhanced MRI volumes serving as ground truth. To overcome severe differences in the breast shape, an image registration was applied. We analyzed the correlation between average sound speed in the breast and the breast density estimated from segmented MRIs and found a positive correlation with R=0.70. Based on the results of the pilot study we now carry out a successive clinical study with 200 patients. For this we integrated our reconstruction methods and image post-processing into a comprehensive workflow. It includes a dedicated DICOM viewer for interactive assessment of fused USCT images. A new preview mode now allows intuitive and faster patient positioning. We updated the USCT system to decrease the data acquisition time by approximately factor two and to increase the penetration depth of the breast into the USCT aperture by 1 cm . Furthermore the compute-intensive reflectivity reconstruction was considerably accelerated, now allowing a sub-millimeter volume reconstruction in approximately 16 minutes. The updates made it possible to successfully image first patients in our ongoing clinical study.

Ultrasound Computer Tomography (USCT), developed at KIT, is a promising new imaging system for breast cancer diagnosis, and was successfully tested in a pilot study. The 3D USCT II prototype consists of several hundreds of ultrasound (US) transducers on a semi-ellipsoidal aperture. Spherical waves are sequentially emitted by individual transducers and received in parallel by many transducers. Reflectivity volumes are reconstructed by synthetic aperture focusing (SAFT). However, straight forward SAFT imaging leads to blurred images due to system imperfections. We present an extension of a previously proposed approach to enhance the images. This approach includes additional a priori information and system characteristics. Now spatial phase compensation was included. The approach was evaluated with a simulation and clinical data sets. An increase in the image quality was observed and quantitatively measured by SNR and other metrics.

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

3D Ultrasound Computer Tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The KIT prototype provides three different modalities: reflectivity, speed of sound, and attenuation. The reflectivity images are reconstructed using a Synthetic Aperture Focusing Technique (SAFT) algorithm. For high-resolution re ectivity images, with spatially homogeneous reflectivity, attenuation correction is necessary. In this paper we present a GPU accelerated attenuation correction for 3D USCT and evaluate the method by means of image quality metrics; i.e. absolute error, contrast and spatially homogeneous reflectivity. A threshold for attenuation correction was introduced to preserve a high contrast. Simulated and in-vivo data were used for analysis of the image quality. Attenuation correction increases the image quality by improving spatially homogeneous reflectivity by 25 %. This leads to a factor 2.8 higher contrast for in-vivo data.

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). The aim of this work was to design a new aperture for our full 3D USCT which extends the properties of the current aperture to a larger ROI fitting the buoyant breast in water and decreasing artifacts in transmission tomography. The optimization resulted in a larger opening angle of the transducers, a larger diameter of the aperture and an approximately homogeneous distribution of the transducers, with locally random distances. The developed optimization methods allow us to automatically generate an optimized aperture for given diameters of apertures and transducer arrays, as well as quantitative comparison to other arbitrary apertures. Thus, during the design phase of the next generation KIT 3D USCT, the image quality can be balanced against the specification parameters and given hardware and cost limitations. The methods can be applied for general aperture optimization, only limited by the assumptions of a hemispherical aperture and circular transducer arrays.

3D ultrasound computer tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The KIT prototype provides three different modalities (reflectivity, speed of sound (SOS), and attenuation). For high resolution reflectivity images phase aberration correction using the SOS images is necessary. The synthetic aperture focusing technique (SAFT) used for reflectivity image reconstruction is highly compute-intensive but suitable for an accelerated execution on GPUs. In this paper we investigate how the calculation of the phase aberration correction can be optimized and integrated into the SAFT algorithm. We analysed different strategies to optimize the trade off between memory requirement and image quality. For 64 slices with 1024 2 pixels a reconstruction can be done in 34 min on eight GPUs with a performance of 58.4 GV/s in comparison to the GPU reconstruction without phase aberration correction which needs 23 min. The average error made by the optimized SOS calculation is negligible.

3D ultrasound computer tomography (USCT) requires a large number of transducers approx. two orders of magnitude larger than in a 2D system. Technical feasibility limits the number of transducer positions to a much smaller number resulting in a sparse aperture and causing artifacts due to grating lobe effects in the images. Usually, grating lobes are suppressed by using a non-sparse geometry. Thus, there is no quantitative estimation method available how much the image contrast is degraded when a sparse aperture is applied and how much the contrast is improved when adding more transducers, changing the overall aperture or the object. In this paper the effect of the grating lobes on the image quality was analyzed for a spherical, a hemispherical and the semi-ellipsoidal USCT aperture: The background noise due to grating lobes is very similar for the three apertures and mainly influenced by the sparseness and the imaged object. A model for noise reduction was fitted to simulated and experimental data, and can be used to predict the peak-signal-to-noise- ratio for a given object and number of aperture positions.

Ultrasound Computer Tomography is an upcoming imaging modality for early breast cancer detection. For evaluation of the method, comparison with the standard method X-ray mammography is of strongest interest. To overcome the significant differences in dimensionality and compression state of the breast, in earlier work a registration method based on biomechanical modeling of the breast was proposed. However only homogeneous models could be applied, i.e. inner structures of the breast were neglected. In this work we extend the biomechanical modeling of the breast by estimating patient-specific tissue parameters automatically from the speed of sound volume. Two heterogeneous models are proposed modeling a quadratic and an exponential relationship between speed of sound and tissue stiffness. The models were evaluated using phantom images and clinical data. The size of all lesions is better preserved using heterogeneous models, especially using an exponential relationship. The presented approach yields promising results and gives a physical justification to our registration method. It can be considered as a first step towards a realistic modeling of the breast.

3D ultrasound computer tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The synthetic aperture focusing technique (SAFT) used for image reconstruction is highly computeintensive but suitable for an accelerated execution on GPUs. In this paper we investigate how a previous implementation of the SAFT algorithm in CUDA C can be further accelerated and integrated into the existing MATLAB signal and image processing chain for 3D USCT. The focus is on an efficient preprocessing and preparation of data blocks in MATLAB as well as an improved utilisation of special hardware like the texture fetching units on GPUs. For 64 slices with 1024×1024 pixels each the overall runtime of the reconstruction including data loading and preprocessing could be decreased from 35 hours with CPU to 2.4 hours with eight GPUs.

Breast cancer is the most common cancer among women. The established screening method to detect breast cancer in an early state is X-ray mammography. However, X-ray frequently provides limited contrast of tumors located within glandular tissue. A new imaging approach is Ultrasound Computer Tomography generating threedimensional volumes of the breast. Three different images are available: reflectivity, attenuation and speed of sound. The correlation of USCT volumes with X-ray mammograms is of interest for evaluation of the new imaging modality as well as for a multimodal diagnosis. Yet, both modalities differ in image dimensionality, patient positioning and deformation state of the breast. In earlier work we proposed a methodology based on Finite Element Method to register speed of sound images with the according mammogram. In this work, we enhanced the methodology to register all three image types provided by USCT. Furthermore, the methodology is now completely automated using image similarity measures to estimate rotations in datasets. A fusion methodology is proposed which combines the information of the three USCT image types with the X-ray mammogram via semitransparent overlay images. The evaluation was done using 13 datasets from a clinical study. The registration accuracy was measured by the displacement of the center of a lesion marked in both modalities. Using the automated rotation estimation, a mean displacement of 10.4 mm was achieved. Due to the clinically relevant registration accuracy, the methodology provides a basis for evaluation of the new imaging device USCT as well as for multimodal diagnosis.

Speed of sound imaging is an important modality used in medical ultrasound applications. We developed a 3D ultrasound computer tomograph (3D USCT) which is capable of reflection and transmission tomography. Most 3D tomography reconstruction methods like the algebraic reconstruction technique rely on the assumption that the transmission rays propagate straightly from emitter to receiver, which is not valid for ultrasound. Due to refractions in the tissue the rays are bent rather than straight. To overcome this problem we use a 3D Eikonal solver that calculates the bent ray paths for the transmission pulses and include it into our Compressive Sampling reconstruction framework. Using an iterative scheme we show results for synthetic and real data. The shape and the outline of the phantoms reconstructed with the bent-ray method match the reflection reconstructions better and for synthetic data the speed of sound is closer to the speed of sound in the phantom by approximately 1.2 m/s.

A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3DUSCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3DUSCT with nearly isotropic 3DPSF, realizing for the first time the full benefits of a 3Dsystem. In this paper results of the 3D point spread function measured with a dedicated phantom and images acquired with a clinical breast phantom are presented. The point spread function could be shown to be nearly isotropic in 3D, to have very low spatial variability and fit the predicted values. The contrast of the phantom images is very satisfactory in spite of imaging with a sparse aperture. The resolution and imaged details of the reflectivity reconstruction are comparable to a 3TeslaMRI volume of the breast phantom. Image quality and resolution is isotropic in all three dimensions, confirming the successful optimization experimentally.

A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3DUSCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3DUSCT with nearly isotropic 3D point spread function, realizing for the first time the full benefits of a 3D system. The 3DUSCT II is based on a semi-ellipsoidal transducer holder cut from polyoxymethylene. The aperture is implemented together with water supply, disinfection unit, temperature control, and movement mechanics in a patient bed. 2041 transducers are mounted in the aperture holder grouped into transducer array systems with embedded amplifiers and emitter electronics. The data acquisition is carried out with 480 parallel channels at 20MHz and with 12 bit resolution. 3.5 million A-Scans with 20 GByte of raw data are acquired for one breast volume. With data acquisition time of less than two minutes for one breast volume, the new system enables the next step of our research: a first clinical study.

At Karlsruhe Institute of Technology a 3D Ultrasound Computer Tomography (USCT) system is under development for early breast cancer detection. With 3.5 million of acquired raw data and up to one billion voxels for one image, the reconstruction of breast volumes may last for weeks in highest possible resolution. The currently applied backprojection algorithm, based on the synthetic aperture focusing technique (SAFT), offers only limited potential for further decrease of the reconstruction time. An alternative reconstruction method could apply signal detected data and rasterizes the backprojected ellipsoids directly. A well-known rasterization algorithm is the Bresenham algorithm, which was originally designed to rasterize lines. In this work an existing Bresenham concept to rasterize circles is extended to comply with the requirements of image reconstruction in USCT: the circle rasterization was adapted to rasterize spheres and extended to floating point parameterization. The evaluation of the algorithm showed that the quality of the rasterization is comparable to the original algorithm. The achieved performance of the circle and sphere rasterization algorithm was 12MVoxel/s and 3.5MVoxel/s. When taking the performance increase due to the reduced A-Scan data into account, an acceleration of factor 28 in comparison to the currently applied algorithm could be reached. For future work the presented rasterization algorithm offers additional potential for further speed up.

Breast cancer is the most common cancer among women. The established screening method to detect breast cancer is X-ray mammography. However, X-ray frequently provides poor contrast of tumors located within glandular tissue. In this case, additional modalities like MRI are used for diagnosis in clinical routine. A new imaging approach is Ultrasound Computer Tomography, generating three-dimensional speed of sound images. High speed of sound values are expected to be an indicator of cancerous structures. Therefore, the combination of speed of sound images and X-ray mammograms may benefit early breast cancer diagnosis. In previous work, we proposed a method based on Finite Elements to automatically register speed of sound images with the according mammograms. The FEM simulation overcomes the challenge that X-ray mammograms show two-dimensional projections of a deformed breast whereas speed of sound images render a three-dimensional undeformed breast in prone position. In this work, 15 datasets from a clinical study were used for further evaluation of the registration quality. The quality of the registration was measured by the displacement of the center of a lesion marked in both modalities. We found a mean displacement of 7.1 mm. For visualization, an overlay technique was developed, which displays speed of sound information directly on the mammogram. Hence, the methodology provides a good basis for multimodal diagnosis using mammograms and speed of sound images. It proposes a guidance tool for radiologists who may benefit from the combined information.

At the Karlsruhe Institute of Technology (KIT) a three-dimensional ultrasound computer tomography (3D USCT) system for early breast cancer diagnosis is being developed. This method promises reproducible volume images of the female breast in 3D. Initial measurements and a simulation based optimization method, which took several physical properties into account, led to a new aperture setup. Yet this simulation is computational too demanding to systematically evaluate the different 'virtual' apertures which can be achieved by rotation and lifting of the system. In optics a Fourier based approach is available to simulate imaging systems as linear systems. For the two apertures used in our project and one hypothetical linear array aperture this concept was evaluated and compared to a reference simulation. An acceptable conformity between the new approach and the reference simulation could be shown. With this approach a fast evaluation of optimal 'virtual' apertures for specific measurement objects and imaging constraints can be carried out within an acceptable time constraint.

Breast cancer is the most common type of cancer for women in Europe and North America. The established standard screening method to detect tumors is X-ray mammography. However, X-ray mammography often has low contrast for tumors located within glandular tissue. A new approach is 3D Ultrasound Computer Tomography (USCT), which is expected to detect small tumors at an early stage. This paper describes the development and the results of Finite Element Method (FEM) simulations of the Transducer Array System (TAS) used in our 3D USCT system. Not all required material parameters were available,so the main challenge of this work was to determine these values. After detailed analysis, a set of material parameters was identified which fits the measured data best. The quality of the simulation was evaluated by comparing the simulated impedance characteristics with measured data of the real TAS. The simulation model provides a powerful tool to analyze the 3D USCT TAS. Furthermore, it is now possible to design and optimize future transducers based on simulation.

Breast cancer is the most common type of cancer among women in Europe and North America. The established screening method to detect breast cancer is X-ray mammography, although X-ray frequently provides poor contrast for tumors located within glandular tissue. A new imaging approach is Ultrasound Tomography generating three-dimensional speed of sound images. This paper describes a method to evaluate the clinical applicability of three-dimensional speed of sound images by automatically registering the images with the corresponding X-ray mammograms. The challenge is that X-ray mammograms show two-dimensional projections of a deformed breast whereas speed of sound images render a three-dimensional undeformed breast in prone position. This conflict requires estimating the relation between deformed and undeformed breast and applying the deformation to the three-dimensional speed of sound image. The deformation is simulated based on a biomechanical model using the finite element method. After simulation of the compression, the contours of the X-ray mammogram and the projected speed of sound image overlap congruently. The quality of the matching process was evaluated by measuring the overlap of a lesion marked in both modalities. Using four test datasets, the evaluation of the registration resulted in an average tumor overlap of 97%. The developed registration provides a basis for systematic evaluation of the new modality of three-dimensional speed of sound images, e.g. allows a greater understanding of tumor depiction in these new images.

At Forschungszentrum Karlsruhe an Ultrasound Computer Tomography system USCT) is under development for early breast cancer detection. To detect morphological indicators in sub-millimeter resolution, the visualization is based on a SAFT algorithm (synthetic aperture focusing technique). The current 3D demonstrator system consists of approx. 2000 transducers, which are arranged in layers on a cylinder of 18 cm diameter and 15 cm height. With 3.5 millions of acquired raw data sets and up to one billion voxels for an image, a reconstruction may last up to months. In this work a performance optimized SAFT algorithm is developed. The used software environment is MathWorks' MATLAB. Several approaches were analyzed: a plain M-code (MATLAB's native language), an optimized M-code, a C-code implementation, and a low-level assembler implementation. The fastest found solution uses an SIMD enhanced assembler code wrapped in the C-interface of MATLAB. Additionally a 10% speed up is gained by reducing the function call overhead. The overall speed up is more than one order of magnitude. The resulting computational efficiency is near the theoretical optimum. The reconstruction time is significantly reduced without losing MATLAB's comfortable development environment.

The point spread function (PSF) of an imaging system may be used as measure for the imaging quality. The PSF usually depends on position and an several other system parameters. Our current 3D imaging system for ultrasound computer tomography consists of a rotatable cylinder with approx. 2000 ultrasound transducers. 3D images are reconstructed by means of synthetic aperture focusing technique (SAFT) using all available emitterreceiver-combinations. No analytical solution exists for determining the spatially varying PSF for arbitrary placement of the transducers. This work derives a new numerical approach for the approximation of the 3D PSF for arbitrary transducer geometries including the beam pattern of the ultrasound transducers, a directional point scatterer model, damping of the breast and arbitrary pulse shapes. As an exemplary application the spatially varying 3D PSF of the current cylindrical geometry is analyzed under idealized conditions (point sources, no damping, and isotropic scattering) and compared to non-idealized results of the PSF analysis. The results show the necessity to take the system specific parameters into account for a realistic prognosis of 3D imaging performance.

The aim of this work is to provide a simulation framework for generation of synthetic tomosynthesis images to be used for evaluation of future developments in the field of tomosynthesis. An anthropomorphic software tissue phantom was previously used in a number of applications for evaluation of acquisition modalities and image post-processing algorithms for mammograms. This software phantom has been extended for similar use with tomosynthesis. The new features of the simulation framework include a finite element deformation model to obtain realistic mammographic deformation and projection simulation for a variety of tomosynthesis geometries. The resulting projections are provided in DICOM format to be applicable for clinically applied reconstruction algorithms. Examples of simulations using parameters of a currently applied clinical setup are presented. The overall simulation model is generic, allowing multiple degrees of freedom to cover anatomical variety in the amount of glandular tissue, degrees of compression, material models for breast tissues, and tomosynthesis geometries.

Ultrasound computer tomography is an imaging method capable of producing volume images with high spatial resolution. The imaged object is enclosed by a cylindrical array of transducers. While one transducer emits a spherical wavefront (pulse), all other transducers are recording the radiofrequency (RF) a-scans simultaneously. Then another transducer acts as the emitter and so on. In this paper we describe the image reconstruction method and an enhanced algorithm for the a-scan preprocessing. The image reconstruction is based on a 'full aperture sum-and-delay' algorithm evaluating the reflected and scattered signals in the a-scans. The a-scans are modelled as the tissue response of the imaged object convoluted with the shape of the ultrasound pulse, which is determined by the transfer function of the transducers and the excitation. Spiking deconvolution and blind deconvolution with different parameters are used to build inverse filters of the ultrasound pulse. Applying the inverse filters to the a-scans results in sharper signals which are used for image reconstruction. Smallest scatterers of 0.1 mm size corresponding to one fifth of the used ultrasound wavelength are visible in the reconstructed images. Compared to conventional b-scans the resulting images show an approximately tenfold better resolution.

Ultrasound computer tomography is an imaging method capable of producing volume images with both high spatial and temporal resolution. The promising results of a 2D experimental setup of an ultrasound computer tomography system with at least 0.25 mm resolution encouraged us to build a new 3D demonstration system. It consists of three parts: a tank containing the sensor system, a data acquisition hardware and a computer workstation for image reconstruction and visualization. For the sensor system we developed and manufactured our own low-cost transducer array emitting or receiving ultrasound signals in three dimensions. To optimize the transducer geometry in respect to aperture angle and pressure amplitude the pressure field was simulated using the ultrasound simulation program Field II. Each transducer arrays system carries 8 emitting and 32 receiving elements with integrated amplifier and address electronics. 192 A-scans can be recorded in parallel by the data acquisition hardware. 48 multiplexing steps are needed to store all A-scans of the 1536 receiving transducers. After recording the data is transmitted to the computer workstation.

The Distorted Born Iterative (DBI) method is used for ultrasound tomography in order to localize and identify malignant breast tissues. This approach begins with the Born approximation to generate an initial prediction of the scattering function. Then, iteratively solves the forward problem for the total field and the inhomogeneous Green’s function, and the inverse problem for the scattering function. The drawback of this method is that the associated inverse scattering problem is ill-posed. We are proposing the Truncated General Singular Value Decomposition (TGSVD) approach as a regularization method for the ill posed inverse problem Xy = b in DBI and comparing it to the well known Truncated Singular Value Decomposition (TSVD). The TGSVD employs generalized SVD (GSVD) of matrix pair (X,L) and is neglecting the smallest, contaminated with noise, generalized singular values, while regularization matrix L (we used the first order derivative operator) is responsible for smoothing the solution. This results in better image quality. We compared the performances of these two methods on simulated phantom and proved that TGSVD produces lower relative error and better reconstructed image.