We developed a new mobile ultrasound device for long-term and automated bladder monitoring without user interaction consisting of 32 transmit and receive electronics as well as a 32-element phased array 3 MHz transducer. The device architecture is based on data digitization and rapid transfer to a consumer electronics device (e.g., a tablet) for signal reconstruction (e.g., by means of plane wave compounding algorithms) and further image processing. All reconstruction algorithms are implemented in the GPU, allowing real-time reconstruction and imaging. The system and the beamforming algorithms were evaluated with respect to the imaging performance on standard sonographical phantoms (CIRS multipurpose ultrasound phantom) by analyzing the resolution, the SNR and the CNR. Furthermore, ML-based segmentation algorithms were developed and assessed with respect to their ability to reliably segment human bladders with different filling levels. A corresponding CNN was trained with 253 B-mode data sets and 20 B-mode images were evaluated. The quantitative and qualitative results of the bladder segmentation are presented and compared to the ground truth obtained by manual segmentation.

Volumetric ultrasound imaging is of great importance in many medical fields, especially in cardiology, but also in therapy monitoring applications. For development of new imaging technologies and scanning strategies, it is crucial to be able to use a hardware platform that is as free and flexible as possible and does not restrict the user in his research in any way. For this purpose, multi-channel ultrasound systems are particularly suitable, as they are able to control each individual element of a matrix array without the use of a multiplexer. We set out to develop a fully integrated, compact 1024-channel ultrasound system that provides full access to all transmission parameters and all digitized raw data of each transducer element. For this purpose, we synchronize four research scanners of our latest “DiPhAS” ultrasound research system generation, each with 256 parallel channels, all connected to a single PC on whose GPUs the entire signal processing is performed. All components of the system are housed in a compact, movable 19-inch rack. The system is designed as a general-purpose platform for research in volumetric imaging; however, the first-use case will be therapy monitoring by tracking radiation-sensitive ultrasound contrast agents.

Several research platforms are available for the development of ultrasound applications and algorithm designs but they are all limited by its digitalization frequency ranging up to 80 MHz for standard medical imaging. Using transducers with mid frequencies above 20 MHz for high resolution (bio-) medical imaging, small animal imaging, skin imaging or non-destructive material testing requires ultrasound devices with higher sampling rates. Based on the ultrasound research platform 'DiPhAS' we realized the high frequency version of the beamformer with a digitalization rate of up to 480 MHz at all 128 channels. Each channel is built individually because no integrated circuits with multiple channels are commercially available for such a high digitalization rate. Transmission can be done with pre-flashed but customizable excitation sequences and output voltage up to 22 Vpp. The received data can be accessed as single element channel data of all 128 channels in parallel and transferred to a PC via Gigabit Ethernet or PCI-Express. Beamforming can be done on a massive parallel computing graphics processor (GPU). Online and offline software packages including closed loop control and filtering interfaces for Matlab, C++ and C# are used to process, analyze and visualize the data to characterize the beamformer. The system was set up successfully and evaluated and characterized for biomedical imaging methods using three 128 element ultrasound arrays (all designed by Fraunhofer IBMT) working at center frequencies of 35 MHz, 52 MHz and 56 MHz. The applications demonstrate the performance of the system to meet real time and signal quality demands for high frequency ultrasound imaging

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