Pregled bibliografske jedinice broj: 1172119
RobUSt–An Autonomous Robotic Ultrasound System for Medical Imaging
RobUSt–An Autonomous Robotic Ultrasound System for Medical Imaging // IEEE Access, 9 (2021), 67456-67465 doi:10.1109/access.2021.3077037 (međunarodna recenzija, članak, ostalo)
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Naslov
RobUSt–An Autonomous Robotic Ultrasound System for
Medical Imaging
Autori
Šuligoj, Filip ; Heunis, Christoff M. ; Sikorski, Jakub ; Misra, Sarthak
Izvornik
IEEE Access (2169-3536) 9
(2021);
67456-67465
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, ostalo
Ključne riječi
Biomedical imaging ; medical robots ; object segmentation ; path planning ; robot control
Sažetak
Medical ultrasound (US) systems are widely used for the diagnosis of internal tissues. However, there are challenges associated with acquiring and interpreting US images, such as incorrect US probe placement and limited available spatial information. In this study, we expand the capabilities of medical US imaging using a robotic framework with a high level of autonomy. A 3D camera is used to capture the surface of an anthropomorphic phantom as a point cloud, which is then used for path planning and navigation of the US probe. Robotic positioning of the probe is realised using an impedance controller, which maintains stable contact with the surface during US scanning and compensates for uneven and moving surfaces. Robotic US positioning accuracy is measured to be 1.19±0.76mm. The mean force along US probe z–direction is measured to be 6.11±1.18N on static surfaces and 6.63±2.18N on moving surfaces. Overall lowest measured force of 1.58N demonstrates constant probe-to-surface contact during scanning. Acquired US images are used for the 3D reconstruction and multi-modal visualization of the surface and the inner anatomical structures of the phantom. Finally, K- means clustering is used to segment different tissues. Best segmentation accuracy of the jugular vein according to Jaccard similarity coefficient is measured to be 0.89. With such an accuracy, this system could substantially improve autonomous US acquisition and enhance the diagnostic confidence of clinicians.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo, Interdisciplinarne biotehničke znanosti
POVEZANOST RADA
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
Profili:
Filip Šuligoj
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus