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3D Ultrasound Computed Tomography (USCT) is an imaging method for early breast cancer detection. The third generation 3 USCT device is developed at Karlsruhe Institute of Technology. The USCT III device has a hemispherical transducer distribution and emits and receives nearly spherical waves. This enables reflection and transmission imaging simultaneously and fully in 3D. The main challenges for the front-end design are to integrate a large number of transducers, to allow high voltage coded excitation, and to receive low amplitude signals with high quality. These challenges were solved using a smart sensor frontend design with a custom application specific integrated circuit (ASIC).

The time response of the ultrasound transducers used in our 3D ultrasound tomography device shows a slight reverberation. This may causes artifacts in the reconstructed images. Loss properties of materials used in the array fabrication have a big impact on their complex vibration behavior. Unfortunately, material parameters for accurate modeling are often not available in literature. Here, we present a method to derive loss properties of polymers and composites and how to include them in a finite element analysis (FEA). The method has three steps: First, an experiment to measure the frequency and thickness dependent sound attenuation. Second, a brute-force fit to a frequency-power law expression to obtain an analytic formulation. Third, a conversion of the sound attenuation to an equivalent structural loss factor. The last step is necessary as acoustic attenuation can not directly be implemented in structural mechanics FEA. We applied the method to derive loss properties of the filler and backing material which we use for our ultrasound transducer arrays. When including the loss factor in the simulation a reverberation is predicted, which matches the measurement well. Hence, considering loss properties allows more accurate modeling of complex vibration behavior. This aids in optimizing our ultrasound transducer array design towards better 3D ultrasound imaging.

A semi-automated packaging process for transducer array manufacturing is presented. As an major innovation, a transducer disc is integrated in a sandwich structure between a printed circuit board (PCB) and an acoustic matching layer. Each of the transducer discs contains 18 lead-zirconium-titanate (PZT) fibres embedded in epoxy. To interconnect the transducer array components, adhesive bonding and automatic pick-and-place processes were used. A pre-series was evaluated by measuring the electro-mechanical impedance (EMI) before and after the assembly. Statistical analysis showed consistent behaviour of the series resonance f s and the electro-mechanical coupling k eff before and after the packaging. This encouraged the manufacturing of 256 arrays. These arrays will now be integrated in an ultrasound computer tomography (USCT) system with 3D scanning aperture for breast cancer imaging. With this system, we intend to bridge the gap towards clinical use of full 3D USCT.

A 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function has been constructed at Institute for Data Processing and Electronic (IPE), Karlsruhe Institute of Technology (KIT). This device is currently applied in clinical studies for breast cancer screening. In this paper, a new method to develop an automated segmentation algorithm for USCT acquired images is proposed. The method employs distance regularized level set evolutionary (DRLSE) active contours along with surface fitting extrapolation and 3D binary mask generation for fully automatic segmentation outcome. In the first stage of the proposed algorithm, DRLSE is applied to those 3D USCT slice images which contain breast and are less affected by noise and ring artifacts named as Cat2. The DRLSE segmentation results are employed to extrapolate the rest of slice images known as Cat1. To overcome defectively segmented slice images, a 3D binary mask is generated out of USCT attenuation images. The 3D binary mask is multiplied by the DRLSE-based segmentation results to form finally segmented 3D USCT images. The method was tested on 12 clinical dataset images. According to F-measure criterion, the proposed method shows higher performance than the previously proposed semiautomatic segmentation one.

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. 3D USCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3D USCT, realizing for the first time the full benefits of a 3D system. 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 3 T MRI volume. Important for the obtained resolution are the simultaneously obtained results of the transmission tomography. The KIT 3D USCT was then tested in a pilot study on ten patients. The primary goals of the pilot study were to test the USCT device, the data acquisition protocols, the image reconstruction methods and the image fusion techniques in a clinical environment. The study was conducted successfully; the data acquisition could be carried out for all patients with an average imaging time of six minutes per breast. The reconstructions provide promising images. Overlaid volumes of the modalities show qualitative and quantitative information at a glance. This paper gives a summary of the involved techniques, methods, and first results.

A promising candidate for sensitive imaging of breast cancer is 3D Ultrasound Computer Tomography (3D USCT). So far its clinical applicability for diagnosis has been limited by the duration of the demanding image reconstruction. In this paper we investigate how signal processing and image reconstruction can be accelerated for diagnosis by using heterogeneous hardware. Additionally, the time and costs for real-time system for a future diagnosis and therapy device is estimated. Reusing the device's built-in FPGA-based data acquisition system (DAQ) through reconfiguration results in a speed-up by a factor of 7 for signal processing and by a factor of 2 for image reconstruction. Applying cutting-edge single FPGAs and GPUs, speed-ups by a factor of 10 (FPGA) and 6 (GPU) for signal processing and 15 (FPGA) and 37 (GPU) for image reconstruction were achieved compared to a recent quad-core Intel Core-i7 CPU. Using quad-core CPUs and a cluster of eight GPUs allowed us for the first time to calculate volumes in less than 30 min with an overall speed-up by a factor of 47, enabling a first clinical study. Based on these results we extrapolated that real-time reconstruction for a therapeutic 3D USCT will be possible in the year 2020 if the trend in density follows the ITRS roadmap.

As today's standard screening methods frequently fail to detect breast cancer before metastases have developed, early diagnosis is still a major challenge. With the promise of high-quality volume images, three-dimensional ultrasound computer tomography is likely to improve this situation, but has high computational needs. In this work, we investigate the acceleration of the ray-based transmission reconstruction by a GPU-based implementation of the iterative numerical optimization algorithm TVAL3. We identified the regular and transposed sparse-matrix-vector multiply as the performance limiting operations. For accelerated reconstruction we propose two different concepts and devise a hybrid scheme as optimal configuration. In addition we investigate multi-GPU scalability and derive the optimal number of devices for our two primary use-cases: a fast preview mode and a high-resolution mode. In order to achieve a fair estimation of the speedup, we compare our implementation to an optimized CPU version of the algorithm. Using our accelerated implementation we reconstructed a preview 3D volume with 24,576 unknowns, a voxel size of (8?mm)3 and approximately 200,000 equations in 0.5?s. A high-resolution volume with 1,572,864 unknowns, a voxel size of (2mm)3 and approximately 1.6 million equations was reconstructed in 23?s. This constitutes an acceleration of over one order of magnitude in comparison to the optimized CPU version. We accelerate a ray-based 3D ultrasound CT reconstruction by GPU processing.By use-case optimized SpMV variants a speedup of one order of magnitude is obtained.We derive the optimal number of GPUs for reconstructions that do not fit on one GPU.A 3D-preview is reconstructed in 0.5 s, a high-resolution volume in 23 s.

A promising candidate for breast cancer imaging is ultrasound computer tomography (USCT). At Karlsruhe Institute of Technology (KIT) a 3D USCT with a semiellipsoidal aperture consisting of several hundreds of US transducers was built. The utilized imaging methods require accurate and reliable temperature information over the measured space and acquisition time. Several methods were applied which improved the temperature accuracy and reliability beyond the hardware defaults by one order of magnitude from ±1°C to approx. 0.005°C beyond the requirement of 0.1°C.

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.

As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming image reconstruction. In this work, we investigate the acceleration of the image reconstruction by GPUs and FPGAs. We compare the obtained performance results with a recent multi-core CPU. We show that both architectures are able to accelerate processing, whereas the GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.

A device for 3D ultrasound computer tomography system is currently under development at KIT with the goal of high-resolution images for early breast cancer detection. With its semi-ellipsoidal positioning of 2041 ultrasound transducers around the breast in space, full 3D images can be reconstructed. Calibration process of such a complex system is very time-consuming and difficult. This paper proposes a Newton's method based self calibration using time-of-flight measurements between each emitter and receiver. One unique feature of this method is the separation of each potential error sources in the system and sequential calibration according to their magnitudes. This enables the analysis of each error component in the system. Simulation and application on real data have both shown sub-wavelength accuracy in the calibration results.

3D Ultrasound Computer Tomography (USCT) aims at early detection of breast cancer. The system was optimized for Synthetic Aperture Focusing Technique (SAFT) using unfocused ultrasound transducers. Due to low SNR of the signals, Coded Excitation (CE) and Matched Filter (MF) are applied. For complex objects the received signals (A-scans) consist of multiple overlaid reflections. The overlaid reflections are difficult to separate due to the system's limited bandwidth which results in side lobes. Non-separable reflections limit the resolution and contrast of the resulting images. Using Huffman Sequences (HS) as CE, a trade-off can be set between the side lobe suppression and loss of main lobe energy. Higher suppression of side lobes results in reduced energy in the CE, i.e. smaller SNR. So an approach has been implemented which suppresses the side lobes, but preserves the energy of CE by designing a Huffman sequences based mismatched filter. Combination of a CE and different filters were evaluated for single reflection and multiple overlaid reflections. The results show high side lobe suppression within limited bandwidth and preserve the SNR.

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.

3D Ultrasound Computer Tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. For reflectivity reconstruction a 3D synthetic aperture focusing technique (SAFT) is used which calculates one reflectivity value for each voxel from about 10 million A-scans. In this work the standard SAFT algorithm is extended to calculate reflectivity characteristics for each voxel in the volume using a directional vector derived from the transducer positions. The reflectivity characteristic is evaluated with in-vivo data and enables new information about the reflecting tissues, e.g. local normals. The contrast of SAFT images of an example breast could be increased by 32% and the data shows potential for tissue classification by comparing reflectivity characteristics. Regardless of calculating twelve-times more data for the simplest case, a performance of 46% of the standard SAFT algorithm on GPU could be reached.

In a first pilot study with 3D Ultrasound Computer Tomography especially the speed of sound images of the breast showed promising results for breast cancer detection. Yet, the resolution of transmission tomography in our system is limited in comparison to the reflectivity volumes. In this paper we describe a setup for an improved device overcoming this limitation. An optimized geometry of the transducers in a sparse distribution improves both the contrast in reflection and contrast and resolution in transmission tomography by nearly an order of magnitude. Furthermore data acquisition is accelerated from 10 to less than 2 minutes. The derived methods, simulation, and measuring results are described.

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.

Ultrasound Computer Tomography (USCT) is a promising modality for breast imaging. We developed and tested the first full 3D USCT system aimed at in-vivo imaging. It is based on approx. 2000 ultrasound transducers surrounding the breast within a water bath. From the acquired signal data, reflectivity, attenuation and sound speed images are reconstructed. In a first in-vivo study we imaged ten patients and compared them to MRI images. To overcome the considerably different breast positioning in both imaging methods, an image registration and image fusion based on biomechanical modeling of the buoyancy effect and surface-based refinement was applied. The resulting images are promising: compared with the MRI ground truth, similar tissue structures can be identified. While reflection images seem to image even small structures, sound speed imaging seems to be the best modality for detecting cancer. The registration of both imaging methods allows browsing the volume images side by side and enables recognition of correlating tissue structures. The first in-vivo study was successfully completed and encourages for a second in-vivo study with a considerably larger number of patients, which is currently ongoing.

The KIT 3D USCT was tested in a pilot study on ten patients. The primary goals of the pilot study were to test the USCT device, the data acquisition protocols, the image reconstruction methods and the image fusion techniques in a clinical environment. The study was conducted successfully; the data acquisition could be carried out for all patients with an average imaging time of six minutes per breast. First reconstructions provide promising images. Overlaid volumes of the modalities show qualitative and quantitative information at a glance. The results led to further optimization of the system and the data acquisition protocol.

A promising candidate for breast cancer imaging is ultrasound computer tomography (USCT). At KIT a 3D USCT with a semi-ellipsoidal aperture consisting of several hundreds of US transducers was built. Spherical waves are sequentially emitted and received. 3D SAFT is applied to reconstruct reflectivity volumes. However, straight forward SAFT imaging leads to blurred images. A post-imaging de-blurring approach applying aperture characteristics is described here and analyzed with a simulation and a clinical data set. A increase of 26% in the mean resolution in imaging simulation with a point scatters was achieved. A increase in resolution with breast images was observed, too.

3D ultrasound computer tomography (3D USCT) promises reproducible high-resolution images for early detection of breast tumors. The KIT 3D USCT provides three different modalities (reflectivity, speed of sound, and attenuation) using 2041 transducers. In this setup, with a diameter of 26 cm and height of 17 cm, ultrasound can travel over long distances up to 52 cm. Phase aberrations (PA) due to speed of sound (SOS) variations inside the measuring object (water, different breast tissues) cause many pulses not to overlap in a distinct voxel for the coherent reflectivity reconstruction. Previous research showed that image quality can be increased significantly performing a PA correction. As no quantitative error assessment was done yet, a simulation based on ray tracing is used to quantify their image degradation caused by PA and the effects of the applied PA correction. This was done with the metrics contrast, resolution and displacement for different positions in the 3D USCT. Our work shows that PA correction significantly restores the image quality.

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.

Summary A promising candidate for imaging of breast cancer is ultrasound computer tomography (USCT). The main advantages of a USCT system are simultaneous recording of reproducible reflection, attenuation and speed of sound volumes, high image quality, and fast data acquisition. The here presented 3D USCT prototype realizes for the first time the full potential of such a device. It is ready for a clinical study. Full volumes of a breast can be acquired in four minutes. In this paper images acquired with a clinical breast phantom are presented. The resolution and imaged details of the reflectivity reconstruction are comparable to a 3 tesla MRI volume of the phantom. Image quality and resolution is isotropic in all three dimensions, confirming the successful implementation experimentally.

We designed and built a 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function, to be tested in a clinical study. The objective of this work was to image two healthy volunteers and to evaluate the USCT volumes in comparison to corresponding Magnetic Resonance Images (MRI). The here presented volumes are reflectivity images generated with 3D synthetic aperture focusing technique. The volunteers were imaged with different parameterizations of the data acquisition. The data acquisition time was between four and twelve minutes. For both volunteers we found that the breast surface and inner structures are clearly shown in the USCT volume and fit the structures given by the MRI.

We have developed a three-dimensional ultrasound computer tomography system (3D USCT) for early breast cancer diagnosis. The method gives reproducible volume images of the female breast in 3D. The optimized aperture and transducer array systems show at the used low ultrasound frequency of 2.5 MHz a very high image quality. In contrast to other methods our system has a nearly isotropic and spatially invariant 3D point spread function (PSF) with a resolution of 240 11m as measured with a 70 11m AI bond wire. By simulated spectra including the experimentally measured noise of transmission tomography it could be shown that structures down to 4 mm could be reconstructed in speed of sound images. The reconstruction of the 3D images in reflection tomography could be accelerated by the use of the multi-core structure of PCs and eight graphical processor units by a factor of 94. For a reconstruction of the reflectivity with 64 layers of 10242 pixels we reduce the computing time from 33 hours to about 21 minutes. In a first clinical study and the images of two healthy probands the observed structures in breasts due to 3D USCT are comparable to images obtained with a clinical MRT.

3D ultrasound computer tomography (USCT) is a new and promising method for early breast cancer diagnosis. An ultrasound computer tomograph was developed by the Karlsruhe Institute of Technology (KIT) and provides a resolution of 0.2 mm. The main components are the semi-ellipsoidal aperture with 628 ultrasound (US) emitters and 1413 US receivers and the 480 input channel data acquisition system. An additional external computing system is used for the time consuming image reconstruction. To reduce the reconstruction time different implementations on massive parallel computing architectures like multicore processor, GPUs and FPGAs were tested. One realization applies reconfiguration of the 60 FPGAs inside the DAQ system. The investigations show significant acceleration of the reconstruction time up to a factor of 15.8 for the latest FPGA generation and 17.6 for a state of the art GPU.

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.

As today's standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming synthetic aperture focusing technique based image reconstruction. In this work, we investigate the acceleration of the image reconstruction by a GPU, and by the FPGAs embedded in our custom data acquisition system. We compare the obtained performance results with a recent multi-core CPU and show that both platforms are able to accelerate processing. The GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.

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 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.

Our 3D Ultrasound Computer Tomograph for breast imaging uses unfocused transducers grouped on a large non-planar aperture and synthetic aperture focusing in 3D. Technical feasibility limits the number of transducer positions to a sparse aperture, causing artifacts due to grating lobe effects in the resulting images. To suppress the artifacts, a median filter is applied to special pressure distributions, which are derived for each image point. After filtering the distributions are summed up for reconstruction. This approach reduces the artifacts significantly. For a phantom of ten nylon threads (0.2 mm diameter) an increase of contrast (SDNR) from 7.6 to 35.9 could be achieved. Also more complex phantoms showed significant reduction. The presented approach is simple and very effective, and can be easily integrated into the applied synthetic aperture focusing technique.

We describe the second generation of a 3D-Ultrasound Computer Tomography (USCT) system. After we achieved in the first generation a device with sub-wavelength resolution and three imaging modalities (reflection, attenuation, speed of sound) and tested it with static phantoms, we developed a device for in-vivo imaging. In the new system the geometry of transducers and their spatial distribution is optimized in respect to uniformity and high value of: contrast, resolution, and illumination. Furthermore we developed new electronics which allows faster DAQ (≤ 2 min) and contains larger and faster FPGAs to use their processing power for data pre-processing.

3D ultrasound computer tomography (3D USCT) is a new imaging method aimed at early breast cancer detection. For synthetic aperture focusing the data is acquired with (nearly) unfocussed ultrasound emission and reception. Therefore the SNR of the data is low and needs to be optimized.

Ultrasound Computer Tomography (USCT) records the interaction of ultrasonic waves with an imaged object from many different angles. The main advantage of such a system is simultaneous recording of reflection, absorption and speed of sound images, and higher image quality with fast data acquisition. Until now, it was not feasible to build a 3D USCT due to the high demands on the required number of transducers, high data rate, and time consuming post-processing. The aim of this first experimental setup for 3D USCT was to analyze the feasibility for breast cancer diagnosis of such a system built with today’s technology and draw conclusions for future setups. The results of this system are presented and discussed in regard of data acquisition, image quality, and duration of image reconstruction. The main conclusion is that 3D USCT is feasible with today’s technology, if a sparse aperture or long DAQ times can be accepted. A setup for a second-generation 3D USCT with the main aim to image volunteers and carry out a small preclinical study is proposed.

At Forschungszentrum Karlsruhe a 3D ultrasound computer tomograph (USCT) for breast cancer diagnosis is currently under development. For many applications, i.e. reconstruction of speed of sound maps, signal denoising,signal compression and calibration, it is necessary to detect pulses and their parameters (center frequency, bandwidth factor, time of arrival, phase and amplitude) accurately and robustly. The pulse detection is demanding due to low signal-to-noise ratios (SNR) caused by unfocused pulses from single emitters. Besides that angle dependent pulse shapes result in ultrasonic echoes which are similar in their center frequency but vary strongly in their bandwidth factor. Additionally, in sum 3.5 million A-scans (20 GB) are acquired, so that the pulse detection has to be fast and efficient. This is achieved by using a fast pre-classifler in order to separate the ultrasonic echoes from the non-white system noise of our system. The detected echoes are then passed individually to a parameter estimation method to determine pulse parameters accurately. An analysis of several classifiers resulted in an alternating decision tree which is both fast and accurate. Classification performance of 95% could be achieved as well as robust parameter estimation with non-white system noise if the SNR is larger than 3 dB. A comparative image reconstruction resulted in significantly sharper images.

Our experimental setup for ultrasound computer tomography (USCT) has a cylindrical aperture with a diameter of 18 cm and height of 15 cm. In this setup ultrasound can travel over long distances up to 50 cm. Phase aberration due to speed of sound variations cause many pulses not to overlap in the reflectivity reconstruction. 3D speed of sound (SOS) maps were calculated using the recorded data and applied for correction. Due to a sparse sampling of the received transmission signals, the resulting speed of sound maps are noisy and of low detail. But the accuracy of the average speed of sound is sufficient for phase aberration correction of the reflection images down to object size of approx. 1 mm and increases the image quality significantly. Our work shows that high resolution USCT is not possible without phase aberration correction using SOS information.

Ultrasound computer tomography (USCT) is an imaging method capable of producing volume images with sub-millimeter resolution and high image quality. The long term goal of the system under construction is 3D imaging for early breast cancer diagnosis. In this paper the first images of a clinical breast phantom are presented and discussed in respect to further modifications of our system

At Forschungszentrum Karlsruhe a 3D ultrasound computer tomograph (USCT) is currently under construction aimed at early breast cancer diagnosis. Ellipsoidal backprojection is applied to reconstruct 3D images. As USCT is a system used for imaging, there is a profound interest in analyzing the image resolution and image quality of this system, especially with respect to its system parameters such as number of the sensors, the geometry of the aperture, applied signal processing, etc. In this paper the results of first assessments of the resolution are presented. The resolution is evaluated in terms of the 2D full width at half maximum (2D FWHM) of the system's 3D point spread function (PSF). Slice images of 3D PSFs have been calculated to assess the spatial variability of the PSF within the current setup of the system. However, calculating these results is very time-consuming, thus an approximative approach for the analysis of the 3D PSF in XY and Z has been developed. This approach allows the analysis of the PSF while changing a variety of system parameters in real time. The long term goal of this project is the optimization of the system parameters with respect to the image quality

At Forschungszentrum Karlsruhe the demonstrator of a new medical imaging system based on 3D ultrasound computer tomography will be available at the beginning of 2005. This system requires not only the recording but also the processing of very large datasets of about 3.5 GBytes. On a single PC the reconstruction of a high resolution volume will take up to several weeks. However the reconstruction process can be parallelized. Our long term goal is to accelerate the reconstruction process significantly by the use of GRID technologies. In this paper we present our approach to parallelize the reconstruction by A-scan-decomposition using Java RMI and Matlab.

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.

In previous work we optimized the aperture of our 3D Ultrasound Computer Tomography (USCT) system with emphasis on reflection tomography. Based on the promising clinical results with speed of sound and attenuation images, the next generation aperture will be upgraded to contain also optimization for transmission tomography. The main changes to be implemented in aperture, transducers, and transducer arrays are: (1) Overall 3D aperture: due to the shape of the buoyant breast a simpler hemispherical aperture can be applied. (2) The diameter of the aperture will be increased and the diameter of the transducers will be decreased for further homogenization of the illumination. (3) The disjunctive sampling of the transducers will be increased and the transducers will be distributed randomly to enhance the uniformity of transmission tomography. (4) Transducers will be connected both as emitters and receivers to decrease the need for mechanical movement of the aperture.