9 results about "Surgical team" patented technology

Various of the disclosed embodiments relate to systems and methods for processing surgical data to facilitate further downstream operations. For example, some embodiments may include machine learning systems trained to recognize whether video from surgical visualization tools, such as endoscopes, depicts a field of view inside or outside the patient body. The system may excise or whiteout frames of video appearing outside the patient so as to remove potentially compromising personal information, such as the identities of members of the surgical team, the patients identity, configurations of the surgical theater, etc. Appropriate removal of such non-surgical data may facilitate downstream processing, e.g., by complying with regulatory requirements as well as by removing extraneous data potentially inimical to further downstream processing, such as training a downstream classifier.

Various embodiments disclosed relate to systems and methods for processing surgical data to facilitate further downstream operations. For example, some embodiments can include a machine learning system trained to identify whether video from a surgical visualization tool, such as an endoscope, depicts a field of view inside or outside a patient’s body. The system can crop or whiten video frames that appear outside the patient to remove potentially leaking personal information, such as the identity of surgical team members, the identity of the patient, the configuration of the surgical room, etc. Proper removal of such non-surgical data can facilitate downstream processing, for example, by complying with regulatory requirements and by removing irrelevant data that can be detrimental to further downstream processing, such as training downstream classifiers.

Medical software tools platforms utilize a surgical display to provide access to specific medical software tools, such as medically-oriented applications or widgets, that can assist surgeons or surgical team in performing various procedures. In particular, an endoscopic camera may register the momentary rise in the optical signature reflected from a tissue surface and in turn transmit it to a medical image processing system which can also receive patient heart rate data and display relevant anomalies. Changes in various spectral components and the speed at which they change in relation to a source of stimulus (heartbeat, breathing, light source modulation, etc.) may indicate the arrival of blood, contrast agents or oxygen absorption. Combinations of these may indicate various states of differing disease or margins of tumors, and so forth. Also, changes in temperatures, physical dimensions, pressures, photoacoustic pressures and the rate of change may indicate tissue anomalies in comparison to historic values.

Various disclosed embodiments provide systems and methods for evaluating surgical team performance during non-operational periods within a surgical site. Specifically, one or more sensors disposed throughout a surgical site may acquire data during non-operational periods, and in some embodiments, data may be acquired at several times of procedures and non-operational periods within the site. The disclosed embodiments segment and analyze the data to infer undesirable or inefficient behavior over non-operational periods between surgical procedures, as well as to improve the progression of behavior. Systems and methods for evaluating various topologies and metrics for non-operating periods, as well as for monitoring and providing feedback are also disclosed.

Systems and methods for analysis and review of surgical videos are disclosed. The systems and methods may include analyzing video frames of prior surgical procedures performed by a particular surgeon to ascertain a skill level of the particular surgeon; accessing a data structure containing patient characteristics associated with the prior surgical procedures; accessing a surgical schedule including prospective surgical procedures overlapping in time; obtaining patient characteristics associated with the prospective surgical procedures; analyzing the plurality of video frames to ascertain an expected amount of time for the particular surgeon to perform a particular prospective surgical procedure; determining requirements for particular prospective surgical procedure; determining whether the particular surgeon meets the requirements; and outputting an indicator that the particular surgeon meets the requirements.

The invention relates to a system and method for surgical data review. Various disclosed embodiments relate to systems and methods for processing surgical data to facilitate further downstream operations. For example, some embodiments may include a machine learning system trained to identify whether a video from a surgical visualization tool, such as an endoscope, depicts a field of view within or outside a patient's body. The system may cut or whiten video frames appearing outside the patient to remove personal information that may be leaked, such as the identity of a surgical team member, the identity of the patient, the configuration of the surgical operating room, and the like. Appropriate removal of such non-surgical data may facilitate downstream processing, for example, by complying with regulatory requirements and by removing irrelevant data that may be disadvantageous for further downstream processing, such as training a downstream classifier.

Various disclosed embodiments provide systems and methods for associating and presenting operating room playback data in order to facilitate more insight analysis and feedback. Specifically, various embodiments present kinematics and system event data collected during surgery, as well as wider operating room context data that can be captured by, for example, a visual imaging system or a depth imaging system within an operating room. In this manner, the auditor can more easily cross-reference data types during playback, differentiating inefficient and one-time anomalous events that persistently affect surgical outcomes. Identifying such distinctions can facilitate the auditor to provide more executable feedback to members of the surgical team. Metrics for assessing surgical performance using cross-reference data are also disclosed.

The present application relates to the field of medical information technology, and more particularly to a surgical duration prediction method and system based on deep expression of cooperation relationship and a storage medium, comprising: constructing a heterogeneous graph according to processing data, defining node types and multiple relationship edges in the heterogeneous graph; designing a heterogeneous graph neural network model, inputting the heterogeneous graph into the heterogeneous graph neural network model, aggregating neighborhood information through a multi-layer information transmission mechanism, and finally generating a surgical node feature representation; based on the surgical node feature representation, predicting the preparation stage duration, operation stage duration and recovery stage duration of the surgery, and performing inverse normalization and effect evaluation on the prediction results to obtain a surgical duration prediction model. The present application deeply expresses the cooperation relationship between medical staff through a heterogeneous graph structure, fully learns the team cooperation mode by using the message passing mechanism of the graph neural network, solves the problem that the traditional method cannot effectively model the complex interaction relationship of the surgical team, and significantly improves the accuracy and practicality of the surgical duration prediction.

Medical software tools platform utilizes a surgical display to provide access to specific medical software tools, such as medically-oriented applications or tools, that can assist those in the operating room, such as a surgeon or surgical team, with a surgery. In particular, an optical sensor located within an endoscopic camera may register subtle differences in color characteristics reflected from a tissue surface and in turn transmit the information to a medical image processing system. Moreover, the new tools are intended to help surgeons better determine the boundaries between healthy and diseased regions during surgical procedures. Various tools are intended to be used in procedures where indocyanine green (ICG) fluorescent dye is used. Intraoperative fluorescence imaging is commonly used during minimally invasive procedures to enable surgeons to visualize tissue perfusion and anatomical structures. The term perfusion refers to the passage of blood and tissue fluid through the capillary bed. Intraoperative fluorescence imaging can also be used to improve visualization of vessels and structures, which, in turn, may reduce the risk of complications during minimally invasive surgeries.