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Item type:Publication, Access status: with files , An AI based mobile robot for autonomous ultrasound in legal medicineComprehensive documentation of internal tissue structures plays an important role in legal medicine. Although ultrasound is widely used in medical diagnostics as a powerful modality for injury detection and documentation, its integration into legal medicine workflows remains limited. Potential reasons include physical strain and infection risks due to manual probe placement at different locations along the body. Robotic ultrasound systems have been proposed to address such challenges. However, current systems are typically restricted to specific target regions and are limited in mobility and autonomy, complicating their clinical integration and fully autonomous, task-level operation. We therefore propose a mobile robotic system for autonomous ultrasound scanning across the body. The system localizes the body, estimates internal target structures, moves to reach the target structure, and performs ultrasound scans. We evaluate the system in three stages. First, we assess the accuracy and robustness of target localization and scan path planning across different body types. Second, we conduct experiments with a body phantom to evaluate the repeatability of covering target structures. Third, we demonstrate the system in a real legal medicine setting. Our experiments demonstrate that the system can approach the body, define the scan path, and acquire reproducible ultrasound images of target structures. These results demonstrate the feasibility of fully autonomous ultrasound imaging across multiple anatomical regions using a mobile robotic system. Beyond legal medicine, the proposed mobile system offers perspectives for autonomous imaging in broader clinical settings such as telemedicine and infectious disease settings, supporting remote diagnostics while reducing infection risks.Publicationtype: Journal Article11 8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A mobile robotic approach to autonomous surface scanning in legal medicinePurpose : Comprehensive legal medicine documentation includes internal and external examination of the corpse. Typically, this documentation is conducted manually during conventional autopsy. Systematic digital documentation would be desirable, especially for external wound examination, which is becoming more relevant for legal medicine analysis. For this purpose, RGB surface scanning has been introduced. While manual full-surface scanning using a handheld camera is time-consuming and operator-dependent, floor or ceiling-mounted robotic systems require specialized rooms. Hence, we consider whether a mobile robotic system can be used for external documentation. Methods : We develop a mobile robotic system that enables full-body RGB-D surface scanning. Our work includes a detailed configuration space analysis to identify the environmental parameters that must be considered for a successful surface scan. We validate our findings through an experimental study in the lab and demonstrate the systems application in legal medicine. Results : Our configuration space analysis shows that a good trade-off between coverage and time is reached with three robot base positions, leading to a coverage of 94.96 %. Experiments validate the effectiveness of the system in accurately capturing body surface geometry with an average surface coverage of 96.90±3.16 % and 92.45±1.43 % for a body phantom and actual corpses, respectively. Conclusion : This work demonstrates the potential of a mobile robotic system to automate RGB-D surface scanning in legal medicine, complementing post-mortem CT scans for inner documentation. Our results indicate that the proposed system can contribute to more efficient, autonomous legal medicine documentation, reducing the need for manual intervention.Publicationtype: Journal Article16 11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A modified da Vinci surgical instrument for optical coherence elastography with deep learning(IEEE, 2024-10-23); ; ; ; Robot-assisted surgery has advantages compared to conventional laparoscopic procedures, e.g., precise movement of the surgical instruments, improved dexterity, and high-resolution visualization of the surgical field. However, mechanical tissue properties may provide additional information, e.g., on the location of lesions or vessels. While elastographic imaging has been proposed, it is not readily available as an online modality during robot-assisted surgery. We propose modifying a da Vinci surgical instrument to realize optical coherence elastography (OCE) for quantitative elasticity estimation. The modified da Vinci instrument is equipped with piezoelectric elements for shear wave excitation and we employ fast optical coherence tomography (OCT) imaging to track propagating wave fields, which are directly related to biomechanical tissue properties. All high-voltage components are mounted at the proximal end outside the patient. We demonstrate that external excitation at the instrument shaft can effectively stimulate shear waves, even when considering damping. Comparing conventional and deep learning-based signal processing results in mean absolute errors of 19.27 kPa and 6.29 kPa for a range of 17 kPa-139 kPa, respectively. These results illustrate that precise quantitative elasticity estimates can be obtained. We also demonstrate quantitative elasticity estimation on ex-vivo tissue samples of heart, liver and stomach, and show that the measurements can be used to distinguish soft and stiff tissue types.Publicationtype: Conference Paper24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optical coherence elastography needle for biomechanical characterization of deep tissue(Springer, 2023); ; ; ; Compression-based optical coherence elastography (OCE) enables characterization of soft tissue by estimating elastic properties. However, previous probe designs have been limited to surface applications. We propose a bevel tip OCE needle probe for percutaneous insertions, where biomechanical characterization of deep tissue could enable precise needle placement, e.g., in prostate biopsy. We consider a dual-fiber OCE needle probe that provides estimates of local strain and load at the tip. Using a novel setup, we simulate deep tissue indentations where frictional forces and bulk sample displacement can affect biomechanical characterization. Performing surface and deep tissue indentation experiments, we compare our approach with external force and needle position measurements at the needle shaft. We consider two tissue mimicking materials simulating healthy and cancerous tissue and demonstrate that our probe can be inserted into deep tissue layers. Compared to surface indentations, external force-position measurements are strongly affected by frictional forces and bulk displacement and show a relative error of 49.2% and 42.4% for soft and stiff phantoms, respectively. In contrast, quantitative OCE measurements show a reduced relative error of 26.4% and 4.9% for deep indentations of soft and stiff phantoms, respectively. Finally, we demonstrate that the OCE measurements can be used to effectively discriminate the tissue mimicking phantoms.Publicationtype: Conference Paper32 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Surface scanning for navigation using high-speed optical coherence tomography(De Gruyter, 2022-07-30); ; ; ; Medical interventions are often guided by optical tracking systems and optical coherence tomography has shown promising results for markerless tracking of soft tissue. The high spatial resolution and subsurface information contain valuable information about the underlying tissue structure and tracking of certain target structures is in principle possible. However, the small field-of-view complicates the selection of suitable regions-of-interest for tracking. Therefore, we extend an experimental setup and perform volumetric surface scanning of target structures to enlarge the field-of-view. We show that the setup allows for data acquisition and that precise merging of the volumes is possible with mean absolute errors from 0.041mm to 0.097mm.Publicationtype: Journal Article42 202