{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T08:32:38Z","timestamp":1772181158261,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T00:00:00Z","timestamp":1632787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["VISIMON"],"award-info":[{"award-number":["VISIMON"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s21196481","type":"journal-article","created":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T21:39:29Z","timestamp":1632865169000},"page":"6481","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Portable Ultrasound Research System for Use in Automated Bladder Monitoring with Machine-Learning-Based Segmentation"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0690-9384","authenticated-orcid":false,"given":"Marc","family":"Fournelle","sequence":"first","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]},{"given":"Tobias","family":"Gr\u00fcn","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]},{"given":"Daniel","family":"Speicher","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]},{"given":"Steffen","family":"Weber","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]},{"given":"Mehmet","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"Department of Urology, Faculty of Medicine, Universit\u00e4tsklinikum Freiburg University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany"}]},{"given":"Dominik","family":"Schoeb","sequence":"additional","affiliation":[{"name":"Department of Urology, Faculty of Medicine, Universit\u00e4tsklinikum Freiburg University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany"}]},{"given":"Arkadiusz","family":"Miernik","sequence":"additional","affiliation":[{"name":"Department of Urology, Faculty of Medicine, Universit\u00e4tsklinikum Freiburg University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany"}]},{"given":"Gerd","family":"Reis","sequence":"additional","affiliation":[{"name":"DFKI\u2014German Research Center for Artificial Intelligence, Trippstadter Stra\u00dfe 122, 67663 Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5710-0825","authenticated-orcid":false,"given":"Steffen","family":"Tretbar","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2191-6053","authenticated-orcid":false,"given":"Holger","family":"Hewener","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Fraunhofer Institute for Biomedical Engineering, 66280 Sulzbach, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1007\/s10877-018-0123-6","article-title":"Non-invasive bladder volume measurement for the prevention of postoperative urinary retention: Validation of two ultrasound devices in a clinical setting","volume":"32","author":"Brouwe","year":"2018","journal-title":"J. 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