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.

A method for characterizing a state of an end effector of an ultrasonic device is disclosed. The ultrasonic device including an electromechanical ultrasonic system defined by a predetermined resonant frequency. The electromechanical ultrasonic system further including an ultrasonic transducer coupled to an ultrasonic blade. The method including applying, by an energy source, a power level to the ultrasonic transducer; measuring, by a control circuit coupled to a memory, an impedance value of the ultrasonic transducer; comparing, by the control circuit, the impedance value to a reference impedance value stored in the memory; classifying, by the control circuit, the impedance value based on the comparison; characterizing, by the control circuit, the state of the electromechanical ultrasonic system based on the classification of the impedance value; and adjusting, by the control circuit, the power level applied to the ultrasonic transducer based on the characterization of the state of the end effector.

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 detecting colon polyps disclosed in the present disclosure includes: (a) receiving an image captured by an endoscope inserted into colon of a test subject; (b) recognizing each image section including colonic mucosa and colonic blood vessels in the image; (c) determining whether a colonic vascular bed is disconnected in each image section; (d) displaying a first visual effect representing a vascular bed in which the colonic blood vessels are disconnected; and (e) displaying a second visual effect representing a continuous vascular bed of the colonic blood vessels, wherein operation (b) is configured to recognize each image section through a deep learning model, which is machine learned based on blood vessel data in a plurality of colonic images of the test subject obtained from external annotators, and a degree of disconnection of the vascular bed and a blood vessel pattern.

A robotic surgical system for treating a patient is disclosed including a surgical tool movable relative to the patient and a user input device including a base and a space joint including a central portion movable relative to the base to effect a motion. The robotic surgical system further includes a control circuit configured to receive a user selection signal indicative of a selection between a first motion scaling profile of the motion of the surgical tool and a second motion scaling profile of the motion of the surgical tool, receive a motion control signal from the user input device indicative of a user input force, and cause the surgical tool to be moved in response to the motion control signal in accordance with the first motion scaling profile or the second motion scaling profile based on the user selection signal. The first motion scaling profile is different than the second motion scaling profile.

An electronic endoscope processor includes a converting means for converting each piece of pixel data that is made up of n (n≥3) types of color components and constitutes a color image of a biological tissue in a body cavity into a piece of pixel data that is made up of m (m≥2) types of color components, m being smaller than n; an evaluation value calculating means for calculating, for each pixel of the color image, an evaluation value related to a target illness based on the converted pieces of pixel data that are made up of m types of color components; and a lesion index calculating means for calculating a lesion index for each of a plurality of types of lesions related to the target illness based on the evaluation values calculated for the pixels of the color image.

The present disclosure is directed towards a video display system and an endoscopic system configured to provide the surgeon with an optimized video image based upon user preference. The video display system includes a first video image displaying a white light video of a surgical site. The first video image has a first predetermined area. A second video image is overlaid on the first video image. The second video image is displayed in a fluorescent light video. The second video image is centered on the surgical site and includes a second predetermined area. The second predetermined area is smaller than the first predetermined area so as to define a boundary of white light video. Thus, the video display system provides the surgeon with the ability to reference the location of the fluorescent light video with respect to anatomical features of the surgical site.

A method and device for multimodal imaging of dermal and mucosal lesions. The method includes using at least two imaging modalities from which one is a 3D scan of the lesion, and, additionally providing information on the distance and angulation between scanning device and the dermis or mucosa and mapping at least the second modality over the 3D data.

An artificial intelligence system is trained and used to detect regions of interest on mechanically-enhanced or otherwise mechanically-altered tissue. An internal imaging device (e.g., endoscope) with a mechanical enhancement element alters tissue from its natural state or orientation such that regions of interest on the tissue may be more clearly distinguished from the surrounding tissue. Images of such mechanically-altered tissue are used to train an artificial intelligence system to detect regions of interest with greater accuracy.

The invention relates to a medical optical system. The medical optical system comprises: —a microendoscope (3) for capturing histological images, each of which displays a microscopic tissue section (16) of a macroscopic tissue region (15) with a tumor (23); and—a classification device (31) for classifying the macroscopic tissue sections (16) displayed in the histological images as at least one respective tissue section that represents the tumor (23) or a tissue section that represents healthy tissue and for outputting a classification result for each classified microscopic tissue section (16). The medical optical system additionally comprises a combination device (37) which generates a macroscopic classification image (43) by combining the classification results, said classification image representing the location of the tumor (23) in the macroscopic tissue region (15).