An esophageal monitoring device includes a camera and, optionally, one or more lights to enable visualization of an interior of a subject's esophagus. Visualization of the interior of the subject's esophagus before and after a left atrial ablation procedure may enable a healthcare provider to determine whether or not the left atrial ablation procedure has damaged the subject's esophagus before the subject experiences any symptoms of such damage. An esophageal monitoring device may also include sensors and/or markers that enable a determination of its location within a subject's esophagus. Such an esophageal monitoring device may be configured for three-dimensional mapping, and enable the generation of an accurate three-dimensional map of the physical relationship between a subject's esophagus and the left atrium of his or her heart. Methods of monitoring a subject's esophagus while a left atrial ablation procedure is being conducted on the subject's heart are also disclosed.

A method for creating surgical simulation information by a computer includes creating a virtual body model corresponding to a body state of a patient for surgery, simulating a specific surgical process on the virtual body model to obtain virtual surgical data, dividing the virtual surgical data into minimum surgical operation units, each unit representing one specific operation, and creating cue sheet data composed of the minimum surgical operation units, wherein the cue sheet data represents the specific surgical process.

A method includes training a machine learning model to generate predicted images to obtain a trained machine learning model, based on: a) pre-treatment training images; b) a plan of treatment; and c) post-treatment training images; where the plan of treatment includes: a) a first mark identifying where to apply a product, b) a first product to be applied at the first mark, and c) a first volume of the first product to be applied at the first mark; generating a predicted post-treatment image by applying the trained predictive visualization machine learning model to a new pre-treatment image, based on: a) a second mark on a new pre-treatment image of the area of a patient, b) a second product to be applied at the second mark, and c) a second volume of the second product to be applied at the second mark; where the predicted images identifies a modified area.

A medical procedure system, including a medical instrument to be inserted into a body part, and including position-tracking transducers to provide position signals, a distal end, and at least one radiopaque marker, a position tracking sub-system to compute a position including at least one location and orientation of the distal end in a position-tracking sub-system coordinate frame responsively to the position signals, a fluoroscope to capture fluoroscopic images of an interior of the body part and the radiopaque marker(s), and a registration sub-system to render, to a display, the captured fluoroscopic images including at least one marker-image of the radiopaque marker(s), and at least one graphical representation indicative of the computed position of the distal end, receive user-alignment input aligning the graphical representation(s) with the marker-image(s), and register the position-tracking sub-system coordinate frame with a coordinate frame of the fluoroscope responsively to the received user-alignment input.

For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.

A device configured to provide a faster and more accurate measurement of depths of holes for placement of bone screws and fastener for bone implant fixation procedures. The device includes a combination of a bone probe for physical examination of a hole drilled in a bone and a depth gauge member for determining a depth of the hole and providing digital measurement of the depth.

An exemplary system includes a memory storing instructions and a processor communicatively coupled to the memory. The processor may be configured to execute the instructions to obtain one or more parameters of a non-robotic device in a surgical space, the non-robotic device engaged by a computer-assisted surgical system; generate, based on at least the one or more parameters of the non-robotic device, guidance content for use by the computer-assisted surgical system to facilitate guided teleoperation of the non-robotic device; and provide the guidance content to the computer-assisted surgical system.

Embodiments of the invention provide systems and methods for providing augmented reality to a surgeon with the steps of acquiring at least one preoperative medical scan image of a region of interest in which the surgery is to be performed and introducing a fiducial device non-invasively or minimal invasively into a body lumen present in the region of interest of a patient. The fiducial device will be in particular introduced into a lumen, which can be clearly identified in the medical scan image. The fiducial device is adapted to emit infrared light either by using infrared light source or by using fluorescent material placed in or in the fiducial device ad to be excited by illumination light or exciting light. After acquiring at least one imaging light live image and one infrared live image the tissue structure of the body lumen with the fiducial device placed therein is clearly detectable within the live image and can reliably registered and matched to the scan image for presenting the overlaid images and to the surgeon.

Surgical systems are provided. The surgical system includes an energy applying surgical instrument configured to apply energy to a natural body lumen or organ. A first scope device is configured to transmit image data of a first scene within a field of view. A second scope device is configured to transmit image data of a second scene within a field of view. A controller is configured to receive the transmitted image data of the first and second scenes and to provide a merged image of first and second scenes, where the merged image facilitates coordination of a location of energy to be applied to an inner surface of a tissue wall at a surgical site relative to an intended interaction location of a second instrument on an outer surface of the tissue wall in a subsequent procedure step at the surgical site.

Systems, devices, and methods for controlling cooperative surgical instruments with variable surgical site access trajectories are provided. Various aspects of the present disclosure provide for coordinated operation of surgical instruments accessing a common surgical site from different approach and/or separate body cavities to achieve a common surgical purpose. For example, various methods, devices, and systems disclosed herein can enable the coordinated treatment of tissue by disparate minimally invasive surgical systems that approach the tissue from varying anatomical spaces and must operate differently, but in concert with one another, to effect a desired surgical treatment.