An image processor selects, when a processing start operation for starting image storage processing is performed, a first image and a second image that satisfy a preset selection condition from a plurality of the first images and a plurality of the second images acquired in a target period including a time when the processing start operation is performed, for the image storage processing. A light source processor performs control to switch, out of a first illumination light beam and a second illumination light beam, one being emitted to the other to emit the other, during a target period.

Vision systems on catheters, cannulas, or similar devices with guiding lumens include receptors distributed in annular areas around respective lumens. Each of the receptors has a field of view covering only a portion of an object environment, and the field of view of each of the receptors overlaps with at least one of the fields of view of the other receptors. A processing system can receive image data from the receptors of the vision systems and combine the image data to construct a visual representation of the object environment.

Registration of a surgical image acquisition device (e.g. an endoscope) using preoperative and live contour signatures of an anatomical object is described. A control unit includes a processor configured to compare the real-time contour signature to the database of preoperative contour signatures of the anatomical object to generate a group of potential contour signature matches for selection of a final contour match. Registration of an image acquisition device to the surgical site is realized based upon an orientation corresponding to the selected final contour signature match.

A system and method for estimating a pose of an imaging device for one or more images is provided.

A computer assisted surgery system comprising an image capture apparatus, a display, a user interface and circuitry, wherein the circuitry is configured to: receive information indicating a surgical scenario and a surgical process associated with the surgical scenario; obtain an artificial image of the surgical scenario; output the artificial image for display on the display; receive permission information via the user interface indicating if there is permission for the surgical process to be performed if the surgical scenario is determined to occur.

A processor device includes an image signal acquisition unit, a display control unit, and a region-of-interest detection mode image processing unit. The image signal acquisition unit acquires an image signal from an endoscope. The region-of-interest detection mode image processing unit detects a region-of-interest from the endoscopic image. The display control unit superimposes a highlight display of the region-of-interest on the endoscopic image and displays the endoscopic image on which the highlight display is superimposed. The processor device determines a visibility of the highlight display from image information of the endoscopic image and the highlight display, and notifies a user of a determination result.

Systems, methods, and instrumentalities are disclosed for switching a control scheme to control a set of system modules and/or modular devices of a surgical hub. A surgical hub may determine a first control scheme that is configured to control a set of system modules and/or modular devices. The surgical hub may receive an input from one of the set of modules or a device located in an OR. The surgical hub may make a determination that at least one of a safety status level or an overload status level of the surgical hub is higher than its threshold value. Based on at least the received input and the determination, the surgical hub may determine a second control scheme to be used to control the set of system modules. The surgical hub may send a control program indicating the second control scheme to one or more system modules and/or modular devices.

The image processing device 1X includes a detection model evaluation means 31X and a display control means 33X. The detection model evaluation means 31X is configured to perform an evaluation on suitability of a detection model for detecting an attention area to be noted based on a captured image Ic in which an inspection target is photographed by a photographing unit provided in an endoscope. The display control means 33X is configured to display candidate area information according to a display mode determined based on a result of the evaluation, the candidate area information indicating one or more candidate areas that are one or more candidates of the attention area, the candidate areas being detected by one or more detection models included in detection model(s) subjected to the evaluation, the candidate area information being superimposed on the captured image Ic which is displayed by a display device 2X.

An image processing apparatus according to a first aspect of the present invention acquires a first image and a second image in a first image acquisition mode, or a second image acquisition mode in which a second image acquisition ratio is higher than in the first image acquisition mode, on the basis of a detection result of a specific target (whether or not a specific target has been detected, what type of specific target). For example, in accordance with whether or not a specific target has been detected and the type of specific target, the first image and the second image can be acquired in the first image acquisition mode in a case where the necessity for acquiring the second image is low, whereas the first image and the second image can be acquired in the second image acquisition mode, in which the second image acquisition ratio is high, in a case where the necessity for acquiring the second image is high.

A method of modeling lungs of a patient includes acquiring computed tomography data of a patient's lungs, storing a software application within a memory associated with a computer, the computer having a processor configured to execute the software application, executing the software application to differentiate tissue located within the patient's lung using the acquired CT data, generate a 3-D model of the patient's lungs based on the acquired CT data and the differentiated tissue, apply a material property to each tissue of the differentiated tissue within the generated 3-D model, generate a mesh of the 3-D model of the patient's lungs, calculate a displacement of the patient's lungs in a collapsed state based on the material property applied to the differentiated tissue and the generated mesh of the generated 3-D model, and display a collapsed lung model of the patient's lungs based on the calculated displacement of the patient's lungs.