Described herein is a video laryngoscope apparatus for inspection of an oral cavity region of a patient is disclosed. The video laryngoscope includes an apparatus body, a camera arm unit configured to receive and releasably attach thereto a disposable laryngoscope blade, a light source coupled to the camera arm unit, a communication unit, and a power source. The apparatus body includes a proximal end and a distal end, and the apparatus body is elongate and configured to be hand-held by an operator of the video laryngoscope. The camera arm unit includes a proximal end and a distal end with a camera, and the proximal end of the camera arm unit is connected to the distal end of the apparatus body utilizing an adjustable rotary position linkage member. The communication unit is connected via a linkage device to the proximal end of the apparatus body, and the power source is housed by the apparatus body.

The technology disclosed herein is directed to a medical manipulator system having a medical device. The medical device such as endoscope or other surgical instrument includes an elongated insertion portion. A holder assembly includes an articulated arm carrying the medical device that is attached thereto and is actuated following movement of the medical device and holds the medical device in a stationary state at a desired position. A position/attitude detection unit detects positions and attitudes of the elongated insertion portion in plurality states into which the medical device is caused to swing about a constraint point. A constraint point estimation unit estimates a position of the constraint point based on the positions and attitudes of the insertion portion as detected by the position/attitude detection unit.

An endoscope system includes an endoscope, a control apparatus to which the endoscope is connected, at least one accessory device used in combination with the endoscope and the control apparatus, and data tags respectively provided in the endoscope and the accessory device. The control apparatus reads first data of the respective data tags, compares second data respectively registered about the endoscope and the accessory device and the first data, and performs warning when the first data and the second data do not coincide.

Methods for guiding a surgical procedure include accessing information relating to a surgical procedure, accessing at least one image of a surgical site captured by an endoscope during the surgical procedure, identifying a tool captured in the at least one image by a machine learning system, determining whether the tool should be changed based on comparing the information relating to the surgical procedure and the tool identified by the machine learning system, and providing an indication when the determining indicates that the tool should be changed.

An arrangement for sterile handling of a non-sterile endoscope in a sterile environment. The arrangement includes a sterile endoscope sheath, and the non-sterile endoscope. The sterile endoscope sheath has an optical element arranged at a distal end of the sterile endoscope sheath. The non-sterile endoscope has an endoscope shaft with an optical element arranged at a distal end of the endoscope shaft.

An object of the present invention is to provide a medical image processing apparatus, an endoscope system, a medical image processing method, and a program that assist a user in estimating an accurate size of a region of interest. A medical image processing apparatus according to an aspect of the present invention is a medical image processing apparatus including a processor. The processor is configured to acquire images in time-series, make a determination of whether a region of interest in each of the images is suitable for size estimation, and report, by using a reporting device, a result of the determination and operation assistance information for improving the result of the determination.

An endoscope apparatus includes a processor. The processor conducts analysis whether an endoscope image has been appropriately captured or not on the basis of the endoscope image. The processor acquires correction restriction information that is at least one of a restriction regarding a size of a lumen of an image-captured portion or a restriction regarding a submucosa state of the image-captured portion. The processor generates correction information regarding correction of image-capturing conditions for allowing the endoscope image to be appropriately captured under a restriction of the correction restriction information in a case where it is analyzed that the endoscope image has not been appropriately captured, and outputs the correction information on a monitor.

A medical image processing device includes a processor, in which the processor acquires an examination image of a subject captured by an endoscope, and identifies an incision suitable site in the subject included in the examination image and performs control for outputting incision suitable site information regarding the incision suitable site on the basis of the examination image, and the identification of the incision suitable site information is performed by using a learning image associated with a position of a muscular layer in the subject.

A medical image processing device acquires a medical image, detects a position of a specific blood vessel having a predetermined thickness or more on the basis of the medical image, and performs control for outputting specific blood vessel position information regarding the position of the specific blood vessel to provide a notification. The detection of the position of a specific blood vessel is performed by using a learning image that is the medical image associated with information regarding a position of at least a part of the specific blood vessel.

Embodiments of a system, a machine-accessible storage medium, and a computer-implemented method are described in which operations are performed. The operations comprising receiving a plurality of image frames associated with a video of an endoscopy procedure, generating a probability estimate for one or more image frames included in the plurality of image frames, and identifying a transition in the video when the endoscopy procedure transitions from a first phase to a second phase based, at least in part, on the probability estimate for the one or more image frames. The probability estimate includes a first probability that one or more image frames are associated with a first phase of the endoscopy procedure.