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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.

At Forschungszentrum Karlsruhe an ultrasound computer tomograph for breast cancer imaging in 3D is under development. The aim of this project is the support of early diagnosis of breast cancer. The process of reconstructing the 20 GB of measurement data into a visual 3D volume is very compute intensive. The reconstruction algorithms are written in Matlab. As a calculation platform we are using grid technologies based on gLite, which provides a powerful computing infrastructure.

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.

This paper presents a method for geometrical and time-delay auto-calibration of an ultrasonic computed tomography (USCT) system. The algorithms used for the calibration are based on the principles similar to the global positioning system (GPS) navigation. Ultrasonic transmitters and receivers in USCT can be viewed like satellite transmitters and mobile receiver units in GPS. However, unlike in GPS, none of the positions of the transmitters or receivers in USCT are assumed to be known and all are the to-be-calibrated unknowns. The presented method is capable of calibrating the positions of all ultrasonic transducers and their individual time delays at once. No calibration phantoms are necessary.

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.

For our current 3D demonstrator system for ultrasound computer tomography (USCT) a synthetic aperture based image reconstruction is implemented whose calculation time is in the order of days. Faster approximations might lead to large errors for our USCT setup which uses many multistatic emitter-receiver combinations. The aim of this work is the analysis of non-linear signal to image mapping for a cylindrical aperture and quantify the errors of computational less complex approximations. Four approaches with increasing computational complexity were implemented, tested with the cylindrical setup and compared to a commonly used linear transducer setup. For the linear aperture the second approximation leads to satisfying results. For the more diverging USCT setup a more accurate approximation is needed: the third approximation, which is still less computational expensive as the ground-truth implementation, gives satisfying results.

The contribution presents some results obtained on the way to checking (and partly complementing) the standard reconstruction procedures in USCT by wave-equation based simulations. Mathematical models emerging from the transparent physical background for both the surrounding fluid and the object tissue are presented, followed by the present results of developing a realistic original finite-element- method based simulation. With respect to the need of comparison with the calibration measurements, a preliminary optimization of initial guesses to boundary conditions at the transducer array is discussed, based on a point-source model. The computational requirements of the procedures are also mentioned together with concrete examples of achieved results.

Am Forschungszentrum Karlsruhe wird ein neuer Ultraschall-Computertomograph (USCT) entwickelt, welcher die Brustkrebsdiagnose entscheidend verbessern soll. Zielsetzung ist die Optimierung des Verfahrens und des Rekonstruktionsalgorithmus ohne Hardwareanderung und durch kontrollierbare Experimente ohne Phantomaufbau. Voraussetzung dafur ist die hinreichende ubereinstimmung der Simulation mit dem realen Experiment. Unter Verwendung von Wave3000, einer kommerziellen Software zur Ultraschallsimulation, wurde in Kombination mit einem Interface die Moglichkeit geschaffen die Schallausbreitung und die Interaktion mit Gewebe in der USCT-Geometrie nachzubilden. Vergleiche von Experiment und Simulation ergaben eine hohe Ubereinstimmung und auch Bildrekonstruktionen lieferten viel versprechende Ergebnisse.

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

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

An evaluation of standard methods for reconstruction of sound velocity maps for Ultrasound Computer Tomography (USCT) is presented. Different approaches for detection of transmission signals and sound velocity reconstruction are compared using a simulated and a measured data set. The sound velocity map of the measured object could be reconstructed with 3.6 m/s difference between the reconstructed and the real sound velocities, which is feasible for improvement of USCT reflection and scattering images. But the images of the reconstructed velocity maps are blurry and full of artifacts, so that they are at this state of the work only of limited use for diagnostic purposes.

Die in dieser Arbeit vorgestellte Bildrekonstruktion der Ultraschall Computertomographie basiert auf der vollstandigen Auswertung aller das Objekt durchdringenden und der im Objekt reflektierten und gestreuten Ultraschallsignale. Die Erzeugung der Ultraschallsignale, ihr Transport, Wechselwirkung mit Materie und die Detektion konnen als lineares System modelliert werden: Der Ultraschallpuls wird mit der Gewebeantwort, der raumlichen Streu- bzw. Reflektivitatsfunktion, gefaltet.

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 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.

Das „Two-Hybrid“-System ist eine genetische Methode fur die Detektion von Protein-Protein-Interaktionen. Dabei werden z. B. Matrizen mit 384 Feldern manuell auf wachsende Hefekolonien untersucht und die Ergebnisse in eine Datenbank eintragen. Die Auswertung ist subjektiv und zeitaufwandig. Die vorliegende Arbeit prasentiert ein erstes computergestutztes System, um digitale Bilder von solchen „Two-Hybrid“-Systemen automatisch auszuwerten. Das System zeigte im Test eine 97-prozentige Effektivitat.

Die Registrierung von Rontgenmammogrammen und MR-Volumina der weiblichen Brust ermoglicht die Unterstutzung multimodaler Brustkrebsdiagnostik durch eine automatische Lokalisierung kleiner Lasionen, die nur in einem der Verfahren sichtbar sind. Unser modellbasierter Registrierungsansatz basiert auf der Deformation eines patientenspezifisch generierten Finite Elemente Modells, welches die massiven Deformationen der Brust wahrend der Rontgenmammographie berucksichtigt. Mit diesem Verfahren konnte die Lokalisierung von Lasionen in sechs klinischen Datensatzen gegenuber eines einfachen rigiden Ansatzes um 78% bzw. 94% verbessert werden.

Fur den Aufbau eines medizinischen Diagnosesystems muss stets ein neues Klassifikationssystem entworfen werden, da keine allgemeine und fur beliebige Probleme verwendendbare Losung existiert. Aufgrund der vielen verschiedenen Kombinationsmoglichkeiten von Merkmalsselektoren und Klassifikatoren ist der Entwurf eines guten Klassifikationssystems meist zeitaufwandig und umstandlich. Hierfur waren bislang keine Softwarehilfsmittel verfugbar. Die Komponentensoftware ICE unterstutzt sowohl den manuellen als auch erstmals den automatischen Entwurf medizinischer Diagnosesysteme, so dass in kurzer Zeit Systeme von guter Qualitat erstellt werden konnen.

Es wird ein Verfahren zur automatischen Registrierung von CT- und MRT-Volumendaten der Leber vorgestellt. Die nicht-rigiden Deformationen wurden mittels Thin-Plate Splines modelliert. Ein Verfahren zur automatischen Berechnung der fur die ThinPlate Spline-Interpolation benotigten Kontrollpunkte wurde entwickelt und implementiert. Zur Optimierung der Registrierungstransformation wurde als Gutemas Mutual Information verwendet.

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.

Major problems in treating breast cancer are the early detection of tumors and accurate biopsy of small volumes of breast (mamma) tissue. This report presents an elastic registration algorithm of two x-ray mammograms and a corresponding magnetic resonance imaging (MRI) volume. To cope with the soft tissue deformation of the breast during mammography, a two-dimensional model of breast deformation behavior is used as an elastic transformation. Normalized mutual information is employed as a measure of similarity. Regions of interest in the uncompressed x-ray mammograms are projected into the MRI volume to determine their three-dimensional origin.

We present a new approach for automatic registration of X-ray mammograms and MR images. Multimodal breast cancer diagnosis is supported by automatic localization of small lesions, which are only visible in the mammograms or the MR image. To cope with the huge deformation of the breast during mammography, a finite element model of the deformable behavior of the breast is applied during the registration. An evaluation of the registration with six clinical data sets resulted in an accurate localization with a mean displacement of 4.3 mm (/spl plusmn/ 1 mm) and 3.9 mm (/spl plusmn/ 1.7 mm) for predicting the lesion position in mammograms and in the MR images, respectively.

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.

One of the most powerful approach in ultrasound tomography (UT) is making use of distorted Born iterative (DBI) method to reconstruct high quality image in order to help locate and identify tumors more precisely. Due to its iterative nature, it begins with Born approximation as the initial guess. Then, it makes use of the inhomogeneous Greens function, as the kernel function, to alternatively calculate the total field for the forward problem and the scattering function for the inverse problem. One principal computational problem involved is that inverse problem is ill-posed, which will result in divergence of the DBI method if inappropriate regularization is used. This paper presents the regularization with truncated total least square (TTLS) where the adaptive algorithm is used to choose the regularization parameter in each iteration of DBI instead of using a fixed truncated value in all the iterations. In order to prevent the solution from being contaminated by noise, adaptive algorithm truncates the smallest singular values while minimizing the loss of signal obtained from transducers. Numerical simulations demonstrate that the proposed adaptive algorithm in conjunction with TTLS outperform TTLS with fixed truncation parameter by effectively reducing the noise and minimizing the relative error.