Learn More
Bipedal walking is not fully understood. Motion generated from methods employed in robotics literature is stiff and is not nearly as energy efficient as what we observe in nature. In this paper, we propose validity conditions for motion adaptation from biological principles in terms of the topology of the dynamic system. This allows us to provide a(More)
STING, a biologically inspired steerable needle robot, has the potential to improve diagnostic and drug delivery therapies in neurosurgery. Real-time path planning for steerable needles remains challenging due to complex kinematic constraints and tissue deformation. Inspired by deformation theory, this paper introduces a(More)
Precise segmentation is a prerequisite for an accurate quantification of the imaged objects. It is a very challenging task in many medical imaging applications due to relatively poor image quality and data scarcity. In this work, we present an innovative segmentation paradigm, named Deep Poincaré Map (DPM), by coupling the dynamical system theory with a(More)
Recently we have observed emerging uses of deep learning techniques in multimedia systems. Developing a practical deep learning system is arduous and complex. It involves labor-intensive tasks for constructing sophisticated neural networks, coordinating multiple network models, and managing a large amount of training-related data. To facilitate such a(More)
A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has emerged as a front-line diagnostic tool for brain tumors without ionizing radiation. Manual segmentation of brain tumor extent from 3D MRI volumes is a very time-consuming task(More)
Steerable needles are a promising technology for minimally invasive surgery, as they can provide access to difficult to reach locations while avoiding delicate anatomical regions. However, due to the unpredictable tissue deformation associated with needle insertion and the complexity of many surgical scenarios, a real-time path planning algorithm with high(More)
Generating natural-looking motion for virtual characters is a challenging research topic. It becomes even harder when adapting synthesized motion to interact with the environment. Current methods are tedious to use, computationally expensive and fail to capture natural looking features. These difficulties seem to suggest that artificial control techniques(More)
Percutaneous intervention is a commonly used surgical procedure for many diagnostic and therapeutic operations. Target motion in soft tissue during an intervention caused by tissue deformation is a common problem, along with needle displacement. In this work, we present a deformation planner that generates continuous curvature paths with a bounded curvature(More)
Steerable needles can improve many medical procedures through their ability to reach targets behind critical or impenetrable anatomical structures, such as blood vessels and bones. However, path planning in real-time is challenging due to complicated kinodynamic constraints and tissue deformation. This paper introduces a parallel path planning algorithm(More)