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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.

To accelerate the process of 3D ultrasound computed tomography, we parallelize the most time-consuming part of a paraxial forward model on GPU, where massive complex multiplications and 2D Fourier transforms have to be performed iteratively. We test our GPU implementation on a synthesized symmetric breast phantom with different sizes. In the best case, for only one emitter position, the speedup of a desktop GPU reaches 23 times when the data transfer time is included, and 100 times when only GPU parallel computing time is considered. In the worst case, the speedup of a less powerful laptop GPU is still 2.5 times over a six-core desktop CPU, when the data transfer time is included. For the correctness of the values computed on GPU, the maximum percent deviation of L2 norm is only 0.014%.

Ultrasound transmission tomography can offer quantitative characterization of breast tissue by reconstructing its sound speed and attenuation images. The image reconstruction process is a nonlinear inverse problem which we iteratively solve using the paraxial approximation of wave equation. The problem is tackled via the Gauss-Newton method yielding a set of linear systems and iteratively solving these linear systems. In this paper, we study multigrid methods for solving these linear systems. We test three multigrid schemes including V-cycle, W-cycle, and full multigrid (FMG), with up to four resolution levels. At each grid level, we use the conjugate gradient (CG) method as a standard solver. Our interest is at first by how far these schemes allow us to reduce the computations alone. For performance evaluation, we compare the multigrid methods with fixed-grid CG method where we directly apply CG on the finest grid. Results show that all tested multigrid methods have an accelerating effect in terms of needing fewer CG iterations on the finest grid. The best-case reduction is 32% for V-cycle, 33% for W-cycle, and 27% for FMG. This means that our multigrid scheme has the potential for significantly reducing reconstruction time for large-scale 2D or 3D images, where the computation cost on the finest grid is very high.

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.

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.