Abstract
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.
Highlights
Ultrasound imaging is a frequently used method for postoperative monitoring of the urinary bladder
Post-operative urinary retention (POUR) is a frequent problem for various reasons that can lead to bladder overdistension and needs rapid detection and medical intervention
Accurate bladder volumes can be extracted from 3D ultrasound data; reliable qualitative information about potential bladder overdistension can already be derived from
Summary
Ultrasound imaging is a frequently used method for postoperative monitoring of the urinary bladder. Depending on the surgical context, different clinical conditions that need close monitoring can occur. Post-operative urinary retention (POUR) is a frequent problem for various reasons (e.g., intravesical blood clotting) that can lead to bladder overdistension and needs rapid detection and medical intervention. Invasive procedures such as catheterization present significant discomfort for patients and can lead to infections or even trauma of the urinary tract. Ultrasound imaging is fully non-invasive and has already shown its potential for bladder monitoring [1,2,3]. Accurate bladder volumes can be extracted from 3D ultrasound data; reliable qualitative information about potential bladder overdistension can already be derived from
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