A training device according to an embodiment may be used for training for surgery using a surgical system that includes: a patient side apparatus including first and second robot arms; and a doctor side control apparatus including first and second input devices configured to operate the first and second robot arms respectively and a display. The training device may include: a training control unit configured to display, on the display, a first virtual surgical instrument that moves in response to operation on the first input device, and a second virtual surgical instrument that moves in response to operation on the second input device; and a storage storing therein a surgical video. The training control unit is configured to display on the display the surgical video stored in the storage with overlaying the first virtual surgical instrument and the second virtual surgical instrument on the surgical video.

A system, method, and apparatus are provided for a robotic system effecting autonomous therapy or treatment of a body having soft and/or hard tissue. A system, method, and apparatus are provided for a robotic control system having a fused sensing stream for predicting the deformation of a robotic end effector and the tissue that the end effector is in contact with using, e.g., a Finite Element Analysis (FEA) model. The model updates provide adjustment parameters for the control system to compensate for changes in the mechanical nature of the robotic end effector and the characteristics and/or movement of the tissue being treated by the robotic end effector.

A differentiable simulator for simulating the cutting of soft materials by a cutting instrument is provided. In accordance with one aspect of the disclosure, a method for simulating a cutting operation includes: receiving a mesh for an object, modifying the mesh to add virtual nodes associated with a predefined cutting plane, optimizing a set of parameters associated with a simulator based on ground-truth data, and running a simulation via the simulator to generate outputs that include trajectories associated with a cutting instrument. Optimizing the set of parameters can include performing inference based on a set of ground-truth trajectories captured using sensors to measure real-world cutting operations. The inference techniques can employ stochastic gradient descent, stochastic gradient Langevin dynamics, or a Bayesian approach. In an embodiment, the simulator can be utilized to generate control signals for a robot based on the simulated trajectories.

Methods and systems are provided useful in various procedures, including hair harvesting and implantation, and further including computer-implemented and/or robotic hair transplantation. Methodologies are provided which enable a tool, such as a hair harvesting or a hair implantation tool, to proceed at least under a partial computer control in a selected direction of travel along a donor or recipient area of the patient, as well as changing direction of travel based on desired harvesting and/or implantation criteria.

Example implementations of the present disclosure relate to method, apparatus, device and computer-readable storage medium for a medical assistance operation. In a method, input data is obtained from an endoscope; and information related to an operation behavior of the endoscope is determined based on the input data. According to the above method, the information related to the operation behaviors of the endoscope may be provided in real time based on the current spot of the endoscope. Accordingly, a medical assistance operation may be further provided to a doctor in real time during the endoscopic examination. Furthermore, corresponding apparatus, device and computer storage medium are also provided.

An interactive and dynamic surgical simulation system may be used in the context of a computer-implemented interactive surgical system. The surgical simulation system may provide coordinated surgical imagining. A processor may be configured to execute a simulation of a surgical procedure. The surgical procedure may be simulated in a simulated surgical environment. The processor may generate a first visual representation and a second visual representation. The first visual representation may be of a first portion of the simulated surgical environment. The second visual representation may also be of the first portion of the simulated surgical environment. The processor may coordinate generation of the first visual representation and the second visual representation such that the first visual representation and the second visual representation correspond to a common event in the surgical procedure. And the processor may present the first visual representation and the second visual representation for user interaction within the simulated surgical environment.

A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains image data rendering a blood vessel of a patient. The processing circuitry performs a fluid analysis on the obtained image data and calculates an index value related to a blood flow in the blood vessel with respect to each of a plurality of positions in the blood vessel. With respect to the index values to be calculated, the processing circuitry selects a position in which a first value is to be obtained from among the plurality of positions or selects a value serving as the first value from among the index values exhibited in positions. The processing circuitry causes a display to display the first value in a predetermined display region thereof used for displaying the first value.

A computing device comprises a memory and a control unit coupled to the memory. The control unit is configured to receive a patient model and identify a plurality of port locations on the patient model for accessing a workspace using a plurality of instruments controlled by a computer-assisted device. For each of the port locations, the control unit determines a collision volume for portions of the computer-assisted device proximal to the port location, a reachability metric, and an anthropomorphic metric. For each combination of the plurality of port locations, the control unit determines a collision metric based on overlaps of the collision volumes for the port locations in the combination, and an aggregate metric for the combination. The control unit is also configured to display one or more of the combinations of the plurality of port locations to a user along with a corresponding aggregate metric.

The inventive subject matter is directed to an artificial intelligence intra-operative surgical guidance system and method of use. The artificial intelligence intra-operative surgical guidance system is made of a computer executing one or more automated artificial intelligence models trained on data layer datasets collections to calculate surgical decision risks, and provide intra-operative surgical guidance; and a display configured to provide visual guidance to a user.

An ablation probe tip 100 having a shaft 102 with an insertion end 104 and an annular aperture 120 near the insertion end 104. A center of ablation 124 is located within the shaft 102 and surrounded by the annular aperture shaft 102. The ablation probe tip 100 may be part of an ablation probe system 50 that includes an ablation source 60 that provides ablation means 62 to the ablation probe tip 100. The center of ablation 124 is a focal region from which the ablation means 62 radiates through the annular aperture 120 to form an ablation zone 150, 160, 170. The system 50 has at least one intra-operative control selected from the group of: ablation zone positioning control, ablation zone shaping control, ablation center control, ablation zone temperature control, guided ablation volume/diameter control, and power loading control.