A system for confirming acquisition of a fluid sample is provided. The system includes a wearable electronic device configured to be worn by a user. The device has a housing, at least one imaging sensor associated with the housing, a data transmission interface for sending data to or receiving data from an external electronic device, a microprocessor for managing the at least one imaging sensor and the data transmission interface, and a program for acquiring and processing images acquired by the at least one imaging sensor. The system further includes a sampling device for collecting a fluid sample in a sample container and at least one identification tag attached to or integrally formed with the sampling device or sample container. The at least one identification tag includes or is associated with a tracking code.

The present disclosure provides a method and system for controlling a medical device. The method for controlling the medical device may include: obtaining information related to the medical device and/or information related to a target object; controlling the medical device based on the information related to the medical device and/or the information related to the target object.

Disclosed are various systems and techniques for tracking surgical tools in a surgical video. In one aspect, the system begins by receiving one or more established tracks for one or more previously-detected surgical tools in the surgical video. The system then processes a current frame of the surgical video to detect one or more objects using a first deep-learning model. Next, for each detected object in the one or more detected objects, the system further performs the flowing steps to assign the detected object to a right track: (1) computing a semantic similarity between the detected object and each of the one or more established tracks; (2) computing a spatial similarity between the detected object and the latest predicted location for each of the one or more established tracks; and (3) attempting to assign the detected object to one of the one or more established tracks based on the computed semantic similarity and the spatial similarity metric.

A method includes accessing a three-dimensional representation of a surgical space and based on the three-dimensional representation, for each object in a first constellation of objects: extracting a first location of the object; detecting a first object type of the object; deriving a first surgical status of the object; calculating a first ranking score of the object based on the first object type and the first surgical status; and storing the first location, the first object type, the first surgical status, and the first ranking score in an object container in a set of object containers. The method also includes selecting a first target object at a first time based on a first target ranking score; articulating a mobile camera to locate a first target location of the first target object; and deriving a trajectory of the first target object based on the set of object containers.

[Object] To improve work efficiency with respect to work using a transparent object, such as a transparent operation tool, for example. [Solution] An image region where an object exists as a target region is detected on the basis of a second captured image, when a first captured image is a captured image obtained by selectively receiving a light of a first wavelength band, and the second captured image is a captured image obtained by selectively receiving a light of a second wavelength band, the captured images being obtained by capturing the object that is transparent for the light of the first wavelength band and is opaque for the light of the second wavelength band. Subsequently, an outline of the object is superimposed on the first captured image on the basis of information of the target region detected by the target detecting unit.

One example method for detecting phases of a surgical procedure via video processing includes accessing a video of the surgical procedure and dividing the video into one or more blocks, each of the blocks containing one or more video frames. For each of the blocks, the method includes applying a prediction model on the video frames of the respective block to obtain a phase prediction for each of the video frames. The prediction model is configured to predict, for an input video frame, one of the plurality of phases of the surgical procedure. The method further includes generating an aggregated phase prediction for the respective block by aggregating the phase predictions of the video frames, and modifying the video of the surgical procedure to include an indication of a predicted phase of the respective block based on the aggregated phase prediction.

A method for computer assisted identification of appropriate anatomical structure for placement of a medical device, comprising: receiving a 3D scan volume comprising set of medical scan images of a region of an anatomical structure where the medical device is to be placed; automatically processing the set of medical scan images to perform automatic segmentation of the anatomical structure; automatically determining a subsection of the 3D scan volume as a 3D ROI by combining the raw medical scan images and the obtained segmentation data; automatically processing the ROI to determine the preferred 3D position and orientation of the medical device to be placed with respect to the anatomical structure by identifying landmarks within the anatomical structure with a pre-trained prediction neural network; automatically determining the preferred 3D position and orientation of the medical device to be placed with respect to the 3D scan volume of the anatomical structure.

In one embodiment of the present disclosure, an example system may receive a plurality of frames from at least one image sensor associated with a mobile device, at least one of the plurality of frames containing an image of a wound; display a real time video including at least a portion of the plurality of frames and a visual overlay indicating a desired position of the wound; detect, based on at least part of the plurality of frames, that the wound is in the desired position; display an indication to move the mobile device in a desired direction; receive motion data from at least one motion sensor associated with the mobile device; detect that the mobile device has moved in the desired direction; and display an additional indication on the mobile device.

A method for computer assisted identification of appropriate anatomical structure for placement of a medical device, comprising: receiving a 3D scan volume comprising set of medical scan images of a region of an anatomical structure where the medical device is to be placed; automatically processing the set of medical scan images to perform automatic segmentation of the anatomical structure; automatically determining a subsection of the 3D scan volume as a 3D ROI by combining the raw medical scan images and the obtained segmentation data; automatically processing the ROI to determine the preferred 3D position and orientation of the medical device to be placed with respect to the anatomical structure by identifying landmarks within the anatomical structure with a pre-trained prediction neural network; automatically determining the preferred 3D position and orientation of the medical device to be placed with respect to the 3D scan volume of the anatomical structure.

Systems and methods for surgical preparation are disclosed. A system may include at least one processor configured to access a repository surgical video footage. The processor may enable a surgeon preparing for a contemplated surgical procedure to input case-specific information corresponding to the contemplated surgical procedure and compare the case-specific information with data associated with the surgical video footage to identify a group of intraoperative events likely to be encountered during the contemplated surgical procedure. The processor may determine that a first set and a second set of video footage from differing patients contain frames associated with intraoperative events sharing a common characteristic and omit the second set from a compilation to be presented to the surgeon and include the first set in the compilation to be presented to the surgeon to enable the surgeon to view a presentation including the compilation.