Intracorporeal needle-based therapeutic ultrasound (NBTU) offers a minimally invasive approach for the thermal ablation of malignant brain tumors, including both primary and metastatic cancers. NBTU utilizes a high-fr...
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MRI-targeted biopsy has shown significant advantages over conventional random sextant biopsy, detecting more clinically significant cancers and improving risk stratification. However, needle targeting accuracy, especi...
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Dynamic maneuvers for legged robots present a difficult challenge due to the complex dynamics and contact constraints. This paper introduces a versatile trajectory optimization framework for continuous-time multi-phas...
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Finite element modeling (FEM) is a critical tool in the design and analysis of piezoelectric devices, offering detailed numerical simulations that guide various applications. While traditionally applied to eigenfreque...
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Precise placement of thermal applicators is crucial for effective tissue ablation in Interstitial Thermal Therapy (ITT). Accurately localizing these applicators, which are often encapsulated within needles, poses a ch...
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ISBN:
(数字)9798331599003
ISBN:
(纸本)9798331599010
Precise placement of thermal applicators is crucial for effective tissue ablation in Interstitial Thermal Therapy (ITT). Accurately localizing these applicators, which are often encapsulated within needles, poses a challenge because the thermal applicators are usually indistinct from the needles in MR (Magnetic Resonance) images. This difficulty necessitates a common clinical strategy of using low-power activation with MR Thermometry to confirm the position of the heating center. We developed and validated an MR thermometry-guided robotic system to enhance applicator insertion accuracy in ITT. The system integrates an MR-conditional robot, iterative MR scanning plane refinement, and live thermal map feedback to localize the heating applicator and improve insertion precision. Automated localization is achieved within 30 seconds of scanning, with the system autonomously adjusting applicator positioning based on localization results. Experimental validation demonstrated substantial improvements in targeting accuracy, achieving a 0.8 mm average and 2 mm maximum error after insertion compensation. The thermal effects were negligible, with the 6-degree rise isotherm limited to a 3.4 mm radius. This system enhances ITT by improving the precision of thermal energy delivery, minimizing damage to healthy tissues, and offering the potential to streamline clinical adoption while providing safer and more effective treatment options.
Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D...
Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D-printed fluidic logic gates, fabricating a valve from thermoplastic polyurethane. We investigate the 3D printing of tubing and introduce a novel extrusion nozzle for tubing production. Our approach significantly reduces the production time for soft fluidic valves from 27 hours using replica molding to 3 hours with FDM printing. We apply our 3D-printed valve to develop optimized XOR gates and D-latch circuits, presenting a rapid and cost-effective fabrication method for fluidic logic gates that aims to make fluidic circuitry more accessible to the soft robotics community.
Precise surgical procedures such as deep brain tumor ablation may benefit from intra-operative image guidance using magnetic resonance imaging (MRI). However, the MRI’s strong magnetic fields and constrained space po...
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This paper introduces DRAGON: Deformable Robot for Agile Guided Observation and Navigation, a free-swimming deformable impeller-powered vectored underwater vehicle (VUV). A 3D-printed wave spring structure directs the...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
This paper introduces DRAGON: Deformable Robot for Agile Guided Observation and Navigation, a free-swimming deformable impeller-powered vectored underwater vehicle (VUV). A 3D-printed wave spring structure directs the water drawn through the center of the robot by an impeller, enabling it to move smoothly in different directions. The robot is designed to have a narrow cylindrical profile to lower drag and improve agility. It has a maximum recorded speed of 2.1 BL/s (body lengths per second) and a minimum cost of transport (COT) of 2.9. The robot has two degrees of freedom (DoFs) and is capable of performing a variety of maneuvers including a full circle with a radius of 0.23 m (1.4 BL) and a figure eight, which it completed in 4.98 s (72.3 °/s) and 10.74 s respectively. We operated the robot, untethered, in various environments to test the robustness of the design and analyze its motion and performance.
Pneumatic soft robots are typically fabricated by molding, a manual fabrication process that requires skilled labor. Additive manufacturing has the potential to break this limitation and speed up the fabrication proce...
Pneumatic soft robots are typically fabricated by molding, a manual fabrication process that requires skilled labor. Additive manufacturing has the potential to break this limitation and speed up the fabrication process but struggles with consistently producing high-quality prints. We propose a low-cost approach to improve the print quality of desktop fused deposition modeling by adding a webcam to the printer to monitor the printing process and detect and correct defects such as holes or gaps. We demonstrate that our approach improves the air-tightness of printed pneumatic actuators while reducing the need for fine-tuning printing parameters. Our approach presents a new option for robustly fabricating airtight, soft robotic actuators.
The interaction between the asymmetric (bevel) tip needle and the surrounding tissue results in the deflection of the needle and causes a significant targeting error in prostate biopsy. Several works have been propose...
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The interaction between the asymmetric (bevel) tip needle and the surrounding tissue results in the deflection of the needle and causes a significant targeting error in prostate biopsy. Several works have been proposed to mitigate this issue. While some have shown promising results, they require complex software and hardware which makes them difficult to deploy for clinical use. In this paper, we present a predictive model-based approach for passive compensation of the bevel tip needles in phantom tissues. We predict the needle deflection by approximating the initial deflection angle and simulating the needle path before insertion. The entry point is then modified based on the predicted deflection. To achieve this, we collected a set of needle insertion data into a gelatin phantom in an MRI study and used the data to find the parameters for the predictive model. The model was then tested in another MRI insertion study, which demonstrated promising results with an average of 75.2% targeting accuracy improvement compared with the uncompensated insertions.
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