Search

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.

aDepartment of Neuroradiology, University of Erlangen-Nurnberg, Schwabachanlage 6, D-91054, Germany bDepartment of Radiology, Division of Molecular and Gender Imaging, Medical University Vienna, Wahringer Gurtel 18–20, A-1090, Vienna, Austria c Karlsruhe Institute of Technology (KIT), Institute for Data Processing and Electronics, Postfach 3640, D-76021 Karlsruhe, Germany d Institute of Diagnostic and Interventional Radiology I, Friedrich-Schiller-University Jena, Erlanger Allee 101, D-07740 Jena, Germany

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.

Purpose 4D co-registration of X-ray- and MR-mammograms (XM and MM) is a new method of image fusion. The present study aims to evaluate its clinical feasibility, radiological accuracy, and potential clinical value. Methods XM and MM of 25 patients were co-registered. Results were evaluated by a blinded reader. Results Precision of the 4D co-registration was “very good” (mean-score [ms]=7), and lesions were “easier to delineate” (ms=5). In 88.8%, “relevant additional diagnostic information” was present, accounting for a more “confident diagnosis” in 76% (ms=5). Conclusion 4D co-registration is feasible, accurate, and of potential clinical value.

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.

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.

Ultrasound Computer Tomography (USCT) is a promising 3D modality for early breast cancer detection, which is expected to provide quantitative imaging. The aim of this paper is to evaluate the quantitative diagnostic value of the USCT images, i.e. sound speed and attenuation images, using X-ray mammograms as ground truth. For this purpose we applied our 2D/3D registration method, which is based on biomechanical modeling of the breast. Mammograms were segmented into fatty, glandular and tumorous tissue. For each tissue, the average sound speed and attenuation in the corresponding USCT images was calculated. Tumorous tissue could be separated from fatty and glandular tissue using a fixed absolute sound speed threshold in all regarded datasets. By combining sound speed and attenuation, the separation between fatty and glandular tissue could be improved. By overlaying sound speed and attenuation information on the mammogram, quantitative and morphological information can be combined for multimodal diagnosis. This may benefit early breast cancer detection in future.

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.

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.

Ultrasound Computer Tomography (USCT) is an upcoming modality for early breast cancer diagnosis, which provides morphological as well as quantitative imaging. In order to compare USCT images to the standard modality X-ray mammography, a 2D/3D registration has to be applied. To analyze the relevance of sound speed images as a quantitative imaging method for tissue characterization, the aim of this paper is to quantify sound speed values of different types of tissue using mammograms as ground truth. Mammograms are segmented and classified into fat, glandular and tumorous tissue. For each tissue class the average sound speed in the registered sound speed image is calculated. The mean absolute sound speed was 1457 m/s for regions segmented as fatty tissue, 1470 m/s for glandular and 1509 m/s for tumorous tissue. For all ten datasets, the sound speed in tumorous tissue was significantly higher than in glandular and fatty tissue. Also glandular and fatty tissue could be separated easily by the absolute sound speed values. By color-coding sound speed, quantitative information from USCT and morphological information from X-ray mammography are fused for combined diagnosis. We believe this method will help radiologists in gaining experience in the reading of USCT images. The combination of diagnostic information is likely to be beneficial to early breast cancer detection.

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.

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.

Grid infrastructures provide large computing resources for grand challenge applications. The Interactive European Grid project developed mechanisms for the interactive and MPI-parallel usage of these resources. This chapter presents in detail an interactive approach that allows API style communication with grid resources and execution of parallel applications using MPI. The RPC API of GridSolve and the middleware gLite are integrated by the software Giggle for resource allocation. Furthermore, we describe the adaption of Giggle and GridSolve to allow the remote execution of MPI applications on RPC basis. Performance measurements are carried out to benchmark the solution. We can show an overhead of only few seconds in contrast to a job submitted via gLite, which can take minutes. We find that our approach is mainly limited by the data transfer rates to the different computing sites.

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.

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.

Ziele: Die Rontgen-Mammographie ist das verbreitetste bildgebende Verfahren zur Brustkrebsfruherkennung. Sie liefert hochauflosende zweidimensionale Projektionsbilder der komprimierten Brust mit gutem Kontrast fur Mikrokalk und begrenztem Kontrast zwischen Tumoren und Drusengewebe. Im Gegenzug liefert die Magnetresonanztomographie (MRT) dreidimensionale Bilder mit hohem Weichteilkontrast und zeigt eine hohe diagnostische Genauigkeit bei fehlender Moglichkeit der Detektion von Mikrokalk. Die Bildfusion von Mammogrammen mit den Volumendaten der MRT verspricht potentiell eine Nutzung der Vorteile beider Verfahren. Methode: Die Herausforderung der Bildfusion besteht zum einen im Unterschied der Dimensionalitat beider Modalitaten, zum anderen in der Deformation, die die Brust wahrend der Rontgen-Mammographie durch Kompression erfahrt. Dies wird bei der Bildfusion durch ein patientenspezifisches biomechanisches Modell berucksichtigt, das basierend auf dem segmentierten MRT-Volumen aufgebaut und einer Simulation der Kompression mit der Finite Elemente Methode unterzogen wird. Die simulierte Deformation wird auf das MRT-Volumen angewendet und ein MRT-Volumen in deformierter Brustform berechnet. Ergebnis: Die Methodik wurde zunachst auf 6 klinische Datensatze angewendet. Dabei lies sich eine mittlere Abweichung der Bildfusion von 3,9mm +/1,7mm erreichen. In mehr als 75% der Falle liegt die Abweichung unter 5mm. Schlussfolgerung: Die Ergebnisse sind sehr vielversprechend. Die Bildfusion wird automatisch durchgefuhrt, die resultierenden Bilder beider Modalitaten sind direkt miteinander vergleichbar. So ist es moglich Lasionen aus einer Modalitat im komplementaren Verfahren zu lokalisieren. Die Kombination beider Modalitaten kann potentiell zu einer sichereren Diagnose und einer spezifischeren Lokalisierung von Lasionen in der Mammadiagnostik beitragen. In einer klinischen Studie werden derzeit mit hoherer Fallzahl die Genauigkeit und Robustheit des Verfahrens sowie der klinische Mehrwert der Bildfusion untersucht.

gLite is one of the largest distributed computing infrastructures in operation. It provides access to hundreds of different clusters - all installed and maintained in different ways. This paper analyses the difficulties which users typically experience when moving from their own workstation via clusters or supercomputers to the grid. Based on that analysis, this paper presents tools, which helps to overcome this gap and introduces an advanced command line interface to the grid.

At Forschungszentrum Karlsruhe, a new imaging system for early diagnosis of breast cancer is currently developed. The 3D Ultrasound Computer Tomography (USCT) is based on approx. 2000 ultrasound transducers which produce 20 GB of raw data consisting of 3.5 mio. A-scans (amplitude scans) for one image. The large number of A-scans, the large amount of data and the complex relationship between raw data and reconstructed image makes analysis, understanding and further development difficult for the scientists and especially for new employees and students. For this reason, an interactive graphical user interface (GUI) was developed using MATLAB. It integrates existent analysis methods and is easily extendable with new functionality via a plugin concept. The software provides several visualization functions for the raw data, the reconstructed 3D images, the USCT aperture and the relationships between them. The software shows the capability of MATLAB as programming language for numerical solutions as well as GUIs and complex software systems. It has a large benefit to the working group by integrating analysis methods and sharing them. The GUI and the visualization of the complex relationships of the USCT reduces the training period for new employees and students.

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.

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.

The KIT 3D USCT surrounds the breast with ultrasound transducers on a 3D aperture and emits and receives nearly spherical wave fronts for synthetic aperture focusing. This full 3D system achieves isotropic 3D resolution, has a nearly spatial invariant point spread function, and allows fast data acquisition. The 3D USCT device is equipped with 2041 ultrasound transducers. The acquisition is carried out by sequentially selecting a single emitter, sending a chirp at 2.5 MHz center frequency and recording the transmitted and reflected waves with all receivers. Rotational and translational movement of the aperture is applied to enhance the image contrast. Up to 40 GB of raw data is acquired with 480 parallel channels for digitization at 12 bit and 20 MHz sampling frequency. In a first pilot study, ten patients with different lesions were imaged. Speed of sound, attenuation, and reflection images of each patient were derived from the raw data. Overlaid volumes of the modalities show qualitative and quantitative information at a glance. The results are promising because the breasts' tissue structures and cancerous lesions could be identified in the USCT images.

The computer gaming industry is traditionally the moving power and spirit in the development of computer visualization hardware and software. This year, affordable and high quality virtual reality headsets became available and the science community is eager to get benefit from it. This paper describes first experiences in adapting the new hardware for three different visualization use cases. In all three examples existing visualization pipelines were extended by virtual reality technology. We describe our approach, based on the HTC Vive VR headset, the open source software Blender and the Unreal Engine 4 game engine. The use cases are from three different fields: large-scale particle physics research, X-ray-imaging for entomology research and medical imaging with ultrasound computer tomography. Finally we discuss benefits and limits of the current virtual reality technology and present an outlook to future developments.