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Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pathological assessments. However, due to limited field of view, it is difficult for clinicians to get a full understanding of the scanned tissues. In this paper, we develop a novel mosaicing framework to assemble all frame sequences into a full view image. First, a hybrid rigid registration that combines feature matching and template matching is presented to achieve a global alignment of all frames. Then, the parametric free-form deformation (FFD) model with a multiresolution architecture is implemented to accommodate non-rigid tissue distortions. More importantly, we devise a robust similarity metric called context-weighted correlation ratio (CWCR) to promote registration accuracy, where spatial and geometric contexts are incorporated into the estimation of functional intensity dependence. Experiments on both robotic setup and manual manipulation have demonstrated that the proposed scheme significantly precedes some state-of-the-art mosaicing schemes in the presence of intensity fluctuations, insufficient overlap and tissue distortions. Moreover, the comparisons of the proposed CWCR metric and two other metrics have validated the effectiveness of the context-weighted strategy in quantifying the differences between two frames. Benefiting from more rational and delicate mosaics, the proposed scheme is more suitable to instruct diagnosis and treatment during optical biopsies.
Implantable technologies should be mechanically compliant with the tissue in order to maximize tissue quality and reduce inflammation during tissue reconstruction. We introduce the development of a flexible and expandable implantable robotic (FEIR) device for the regenerative elongation of tubular tissue by applying controlled and precise tension to the target tissue while minimizing the forces produced on the surrounding tissue.

We introduce a theoretical framework based on iterative beam theory static analysis for the design of an expandable robot with a flexible rack. The model takes into account the geometry and mechanics of the rack to determine a trade-off between its stiffness and capability to deliver the required tissue tension force. We empirically validate this theory on the benchtop and with biological tissue.

We show that FEIR can apply the required therapeutical forces on the tissue while reducing the amount of force it applies to the surrounding tissues as well as reducing self-damage.

The study demonstrates a method to develop robots that can change size and shape to fit their dynamic environment while maintaining the precision and delicacy necessary to manipulate tissue by traction.

The method is relevant to designers of implantable technologies. The robot is a precursor medical device for the treatment of Long-Gap Esophageal Atresia and Short Bowel Syndrome.
The method is relevant to designers of implantable technologies. The robot is a precursor medical device for the treatment of Long-Gap Esophageal Atresia and Short Bowel Syndrome.Robot-assisted minimally invasive surgical (MIS) techniques offer improved instrument precision and dexterity, reduced patient trauma and risk, and promise to lessen the skill gap among surgeons. These approaches are common in general surgery, urology, and gynecology. However, MIS techniques remain largely absent for surgical applications within narrow, confined workspaces, such as neuroendoscopy. The limitation stems from a lack of small yet dexterous robotic tools. In this work, we present the first instance of a surgical robot with a direct magnetically-driven end effector capable of being deployed through a standard neuroendoscopic working channel (3.2 mm outer diameter) and operate at the neuroventricular scale. We propose a physical model for the gripping performance of three unique end-effector magnetization profiles and mechanical designs. selleck inhibitor Rates of blocking force per external magnetic flux density magnitude were 0.309 N/T, 0.880 N/T, and 0.351 N/T for the three designs which matched the physical model's prediction within 14.9% error. The rate of gripper closure per external magnetic flux density had a mean percent error of 11.2% compared to the model. The robot's performance was qualitatively evaluated during a pineal region tumor resection on a tumor analogue in a silicone brain phantom. These results suggest that wireless magnetic actuation may be feasible for dexterously manipulating tissue during minimally invasive neurosurgical procedures.Tactile information about an object can only be extracted from population responses of tactile receptors and their afferents. Thus, to best control tactile information in robots, neuroprostheses or haptic devices, inputs should represent responses from full populations of afferents. Here, we describe a simplified model that recreates afferent population responses of thousands of tactile afferents in a personal computer. The whole model includes a resistance network model to simplify the skin mechanics and an improved version of a single unit model that we have previously described. The whole model was implemented by short and efficient python code. The parameters of the model were fit based on a simple vibrating stimulus, but the simulated outputs generalize to match receptive field sizes, edge enhancement, and neurophysiological responses to dot textures, embossed letters and curved surfaces. We discuss how to use this work to model haptic perception and provide guidance in designing and controlling highly realistic tactile interfaces in robots, neural prostheses and haptic devices.
Cochlear implant impedances are influenced by the intracochlear position of the electrodes. Herein, we present an intuitive approach to calculate tissue resistances from transimpedance recordings, ultimately enabling to estimate the insertion depth of cochlear implant electrodes.

Electrode positions were measured in computed-tomography images of 20 subjects implanted with the same lateral wall cochlear implant model. The tissue resistances were estimated from intraoperative telemetry data using bivariate spline extrapolation from the transimpedance recordings. Using a phenomenological model, the electrode insertion depths were estimated.

The proposed method enabled the linear insertion depth of all electrodes to be estimated with an average error of 0.76 ± 0.53 mm.

Intraoperative telemetry recordings correlate with the linear and angular depth of electrode insertion, enabling estimations with an accuracy that can be useful for clinical applications.

The proposed method can be used to objectively assess surgical outcomes during and after cochlear implantation based on non-invasive and readily available telemetry recordings.
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