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

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

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

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

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

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 (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.

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.

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.