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Thermal Ablation Therapy Control with Tissue Necrosis-driven Temperature Feedback Enabled by Neural State Space Model with Extended Kalman Filter

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Thermal Ablation Therapy Control with Tissue Necrosis-driven...

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ryo Murakami Satoshi Mori Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA The United States Department of Biomedical Engineering Robotics Engineering and Computer Science Engineering Worcester Polytechnic Institute Worcester MA The United States

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Thermal ablation therapy is a major minimally invasive treatment. One of the challenges is that the targeted region and therapeutic progression are often invisible to clinicians, requiring feedback provided in numerical information or imaging. Several emerging imaging modalities offer visualization of the ablation-induced necrosis formation; however, relying solely on necrosis monitoring can result in tissue overheating and endangering patients. Some of the necrosis monitoring modalities are known for their capabilities in temperature sensing, but the principles on which they are based have several limitations, such as sensitivity to the tissue motion and their environment. In this study, we propose a necrosis progression-based temperature estimation technique as an added safety feature for avoiding overheating. This model-based method does not require additional sensing hardware. It is designed to work as an independent estimator or a complimentary estimation component with other thermometers for improved robustness. For this objective, the Neural State Space model is used to approximate the ablation therapy, whose theoretical models involve nonlinear partial differential equations. Then, the Extended Kalman Filter is designed based on the model. The simulation study shows the estimation module robustly estimates the tissue temperature under several types of noise. The maximum estimation error observed before terminating ablation was around 1 °C, and the desired safety feature was successfully demonstrated. The estimator is expected to be used in a variety of necrosis monitoring modalities to guarantee more precise and safer treatment. More ambitiously, the architecture with the Neural State Space model and Extended Kalman Filter is generalizable to other medical/biological procedures involving nonlinear and patient/environment-specific physics and even to procedures having no reliable theoretical models.

关键词： Thermometers Estimation Medical treatment Mathematical models Robustness Sensors Safety Temperature control Kalman filters Monitoring

Enhanced Necrosis Visualization in Liver Ablation Monitoring with Fiber Artifact Removal: A Cadaver Study

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Enhanced Necrosis Visualization in Liver Ablation Monitoring...

Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Hua, Yanbo Gao, Shang Ma, Xihan Bhagavatula, Sharath K. Liu, Guigen Jonas, Oliver Zhang, Haichong K. Department of Robotics Engineering Worcester Polytechnic Institute MA United States Department of Biomedical Engineering Worcester Polytechnic Institute MA United States Department of Computer Science Worcester Polytechnic Institute MA United States Department of Radiology Brigham and Women's Hospital Harvard Medical School MA United States

ISBN: (纸本)9781510685949

Surgical resection is a common treatment for liver cancers. When tumors are unresectable, minimally invasive percutaneous radiofrequency ablation (RFA) is an alternative treatment option. Yet, due to challenges in monitoring ablation boundaries, RFA treatment often has a higher recurrence rate. Medical ultrasound (US) imaging is a frequently used tool to oversee various surgical and interventional procedures. However, US imaging has insufficient contrast to visualize ablation-induced necrosis in RFA procedures. This study explores the use of spectroscopic photoacoustic (sPA) imaging techniques leveraging a customized diffusing fiber to enhance the visualization of ablation-induced lesions. While the diffusing fiber enables wide-area illumination, artifacts caused by nonuniform illumination originating from sidelobe interference pose a challenge. Therefore, we implemented the standard Hough Transform (SHT) method to suppress these artifacts, improving the accuracy of necrotic mapping. Using a swine cadaver model, the sPA imaging system demonstrated its capability to identify ablation-induced necrosis, with results confirmed by gross pathology. The detected ablation-induced lesion was measured at 7.81 mm by 6.31 mm in PA imaging, closely aligning with the 7.93 mm average diameter based on pathology. These findings indicate that our approach effectively suppresses artifacts and accurately identifies ablated regions underneath the skin surface. This study concludes that PA-guided ablation could be a viable tool in clinical practice to improve the precision and hence patient outcome of liver RFA procedures. © 2025 SPIE

关键词： Ablation Lesion Indexing Cadaver Study Diffusing Fiber Hough Transform Image-Guided Intervention Photoacoustic Imaging RF Ablation Tuber Ablation

Image-Based Roadmaps for Vision-Only Planning and Control of Robotic Manipulators

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arXiv 2025年

作者： Chatterjee, Sreejani Gandhi, Abhinav Calli, Berk Chamzas, Constantinos Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

This work presents a motion planning framework for robotic manipulators that computes collision-free paths directly in image space. The generated paths can then be tracked using vision-based control, eliminating the need for an explicit robot model or proprioceptive sensing. At the core of our approach is the construction of a roadmap entirely in image space. To achieve this, we explicitly define sampling, nearest-neighbor selection, and collision checking based on visual features rather than geometric models. We first collect a set of image-space samples by moving the robot within its workspace, capturing keypoints along its body at different configurations. These samples serve as nodes in the roadmap, which we construct using either learned or predefined distance metrics. At runtime, the roadmap generates collision-free paths directly in image space, removing the need for a robot model or joint encoders. We validate our approach through an experimental study in which a robotic arm follows planned paths using an adaptive vision-based control scheme to avoid obstacles. The results show that paths generated with the learned-distance roadmap achieved 100% success in control convergence, whereas the predefined image-space distance roadmap enabled faster transient responses but had a lower success rate in convergence. © 2025, CC BY.

关键词： Transient analysis

Occlusion-Based Cooperative Transport for Concave Objects with a Swarm of Miniature Mobile Robots

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arXiv 2024年

作者： Nirgude, Sanjuksha Nema, Animesh Jagetia, Aishwary Robotics Engineering Department Worcester Polytechnic Institute WorcesterMA United States

An occlusion based strategy for collective transport of a concave object using a swarm of mobile robots has been proposed in this paper. We aim to overcome the challenges of transporting concave objects using decentralized approach. The interesting aspect of this task is that the agents have no prior knowledge about the geometry of the object and do not explicitly communicate with each other. The concept is to eliminate the concavity of the object by filling a number of robots in its cavity and then carry out an occlusion based transport strategy on the newly formed convex object or"pseudo object". We divide our work into two parts- concavity filling of various concave objects and occlusion based collective transport of convex objects. © 2024, CC0.

关键词： Mobile robots

Expansion-GRR: Efficient Generation of Smooth Global Redundancy Resolution Roadmaps

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Expansion-GRR: Efficient Generation of Smooth Global Redunda...

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhuoyun Zhong Zhi Li Constantinos Chamzas Department of Robotics Engineering Worcester Polytechnic Institute (WPI) Worcester MA USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Global redundancy resolution (GRR) roadmap is a novel concept in robotics that facilitates the mapping from task space paths to configuration space paths in a legible, predictable, and repeatable way. Such roadmaps could find widespread utility in applications such as safe teleoperation, consistent path planning, and motion primitives generation. However, previous methods to compute GRR roadmaps often necessitate a lengthy computation time and produce non-smooth paths, limiting their practical efficacy. To address this challenge, we introduce a novel method EXPANSION-GRR that leverages efficient configuration space projections and enables a rapid generation of smooth roadmaps that satisfy the task constraints. Additionally, we propose a simple multi-seed strategy that further enhances the final quality. We conducted experiments in simulation with a 5-link planar manipulator and a Kinova arm. We were able to generate the GRR roadmaps up to 2 orders of magnitude faster while achieving higher smoothness. We also demonstrate the utility of the GRR roadmaps in teleoperation tasks where our method outperformed prior methods and reactive IK solvers in terms of success rate and solution quality.

关键词： Limiting Redundancy Manipulators Path planning Intelligent robots

Multilateral Multimodal Human-Robot Collaboration for Robotic Nursing Assistance: Prototype System and Preliminary User Study

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Multilateral Multimodal Human-Robot Collaboration for Roboti...

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Lorena Maria Genua Nikita Boguslavskii Zhi Li Robotics Engineering Department Worcester Polytechnic Institute (WPI) Worcester MA USA

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

In this paper, we introduce an innovative robotic nursing assistance system with multilateral multimodal human-robot (MMHR) collaboration, enabling nursing robots to be assisted by remote and on-site operators. Through our augmented reality (AR) interfaces, the remote and local operators can monitor the robots’ operations, issue task and action commands, and facilitate collaborative assistance and information exchange via AR cues or verbal communication. Our preliminary user study evaluated the usability of the prototype system and validated the efficacy of our MMHR collaboration in a representative nursing assistance task scenario. The results show significant improvements in overall task efficiency for the remote operator and reveal human strategies and rationales in the spontaneous multilateral human-robot collaboration.

关键词： Collaboration Prototypes Human-robot interaction Medical services Usability Robots Monitoring Information exchange Augmented reality

A-SEE2.0: Active-Sensing End-Effector for Robotic Ultrasound Systems with Dense Contact Surface Perception Enabled Probe Orientation Adjustment

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arXiv 2025年

作者： Zhetpissov, Yernar Ma, Xihan Yang, Kehan Zhang, Haichong K. Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Department of Biomedical Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Conventional freehand ultrasound (US) imaging is highly dependent on the skill of the operator, often leading to inconsistent results and increased physical demand on sonographers. Robotic Ultrasound Systems (RUSS) aim to address these limitations by providing standardized and automated imaging solutions, especially in environments with limited access to skilled operators. This paper presents the development of a novel RUSS system that employs dual RGB-D depth cameras to maintain the US probe normal to the skin surface, a critical factor for optimal image quality. Our RUSS integrates RGB-D camera data with robotic control algorithms to maintain orthogonal probe alignment on uneven surfaces without preoperative data. Validation tests using a phantom model demonstrate that the system achieves robust normal positioning accuracy while delivering ultrasound images comparable to those obtained through manual scanning. ASEE2.0 demonstrates 2.47 ± 1.25 degrees error for flat surface normal-positioning and 12.19 ± 5.81 degrees normal estimation error on mannequin surface. This work highlights the potential of A-SEE2.0 to be used in clinical practice by testing its performance during in-vivo forearm ultrasound examinations. © 2025, CC BY.

关键词： Medical robotics

Kinematics & Dynamics Library for Baxter Arm

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arXiv 2024年

作者： Kumar, Akshay Sahasrabudhe, Ashwin Perugu, Chaitanya Nirgude, Sanjuksha Murugan, Aakash Department of Robotics Engineering Worcester Polytechnic Institute United States

The Baxter robot is a standard research platform used widely in research tasks, supported with an SDK provided by the developers, Rethink robotics. Despite the ubiquitous use of the robot, the official software support is sub-standard. Especially, the native IK service has a low success rate and is often inconsistent. This unreliable behavior makes Baxter difficult to use for experiments and the research community is in need of a more reliable software support to control the robot. We present our work towards creating a Python based software library supporting the kinematics and dynamics of the Baxter robot. Our toolbox contains implementation of pose and velocity kinematics with support for Jacobian operations for redundancy resolution. We present the implementation and performance of our library, along with a comparison with PyKDL. © 2024, CC0.

关键词： Redundant manipulators

Feasibility of Pointcloud-based Ultrasound-CT Registration towards Automated, Robot-Assisted Image-Guidance in Spine Surgery*

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Feasibility of Pointcloud-based Ultrasound-CT Registration t...

International Symposium on Medical robotics (ISMR)

作者： Xihan Ma Xiao Zhang Yang Wang Christopher Nycz Arno Sungarian Songbai Ji Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA University of Massachusetts Memorial Medical Center Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering and the Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350377118

ISBN: (纸本)9798350377125

Image-guidance has been shown to improve spine surgical accuracy and patient outcome. Such image guidance can be achieved by registering low-cost, realtime, and radiation-free intraoperative ultrasound (US) with preoperative computed tomography (CT). Employing robotic US system (RUSS) allows automated acquisition of a wide 3D volume, facilitating efficient and accurate registration with CT. However, the registration between CT and robotic 3D US remains an open problem mainly due to (i) the lack of relevant testbed and dataset, and (ii) the modality discrepancy between CT and US. To address these challenges, we present a custom-built lumbar spine phantom for multimodal imaging with rigidly attached fiducials. The phantom is scanned by CT and in-house RUSS. A novel pointcloud-based registration pipeline is presented to register CT and robotic 3D US data of the spine phantom. Preliminary experiments demonstrate efficient (0.53 ± 0.02 seconds) registration of the lumbar spine with an accuracy of 3.57 mm in terms of fiducial registration error (FRE), which is robust to varying initial alignment of the pointclouds. These results show initial feasibility of adopting the proposed registration pipeline in robotic US guided spine surgery. Future work includes further evaluation of registration performance in ex vivo spine samples with denser US acquisitions to further improve registration accuracy.

关键词： Accuracy Three-dimensional displays Ultrasonic imaging Medical robotics Computed tomography Spine Pipelines