An insertion support system includes a state acquisition apparatus configured to acquire first information. The first information includes at least one of: a plurality of pieces of position information related to a plurality of positions of an insertion section to be inserted into an insertion target body; and a plurality of pieces of direction vector information in a longitudinal axis direction of the insertion section. The insertion support system also includes a support information calculator configured to calculate second information related to a rotation quantity of the insertion section based on the first information, and an output section configured to output the second information.

A computer-implemented system is provided that receives a real-time video captured from a medical image device during a medical procedure. The real-time video may include a plurality of frames. The system may be adapted to detect an object of interest in the plurality of frames and apply one or more neural networks configured to identify a plurality of characteristics of the detected object of interest, such as classification, size, and/or location. In some embodiments, the system is adapted to identify, based on one or more of the plurality of characteristics, a medical guideline and present, in real-time on a display device during the medical procedure, information for the medical guideline.

There are provided a learning apparatus, a learning method, an image processing apparatus, an endoscope system, and a program that enable generation of training data on the basis of output data from a learning model for which learning is performed by using normality data. A first learning model (500) is generated by performing first learning using normality data (502) as learning data or by performing first learning using as learning data, normality mask data (504) that is generated by making a part of normality data be lost, and second training data to be applied to a second learning model that identifies identification target data is generated by using output data output from the first learning model in response to input of abnormality data to the first learning model.

An image acquisition unit sequentially acquires a medical image. A recognition processing unit applies a recognition process to the medical image. A recognition result display determination unit determines to display or not display the result of the recognition process on a display according to blur in the medical image. A display control unit controls the display of the recognition process according to the determination by the recognition result display determination unit.

A system for displaying medical imaging data comprising one or more data inputs, one or more processors, and one or more displays, wherein the one or more data inputs are configured for receiving first image data generated by a first medical imaging device, wherein the first image data comprises a field of view (FOV) portion and a non-FOV portion, and the one or more processors are configured for identifying the non-FOV portion of the first image data and generating cropped first image data by removing at least a portion of the non-FOV portion of the first image data, and transmitting the cropped first image data for display in a first portion of the display and additional information for display in a second portion of the display.

A system for controlling a medical image capture device during surgery is provided, the system including circuitry configured to acquire first image data from the medical image capture device, the first image data being of an appearance of a surgical scene at a first instance of time; determine, based on a predicted appearance of the surgical scene based on the first image data at a second instance of time after the first instance of time, one or more desired image capture properties of the medical image capture device; and control the medical image capture device at a third instance of time, the third instance of time being between the first instance of time and the second instance of time, in accordance with the one or more desired image capture properties of the medical image capture device.

An image capturing apparatus includes: a columnar main body having proximal and distal ends, and having a predetermined length therebetween so as to enable insertion of at least the distal end into an oral cavity; at least one light source provided on the proximal or distal end side of the main body, or to the main body, configured to emit light having a predetermined frequency band; a diffuser plate provided on the proximal or distal end side of the main body, or to the main body, configured to diffuse the emitted light toward the oral cavity; and a camera provided on the proximal or the distal end side of the main body, or to the main body, configured to capture an object image based on reflected light which has been diffused by the diffuser plate and reflected from the oral cavity.

Provided herein are systems, methods, and media capable of determining estimated force applied on a target tissue region to enable tactile feedback during interaction with said target tissue region.

A medical system includes a processor. The processor is configured to calculate a presence probability of a lesion in a not-yet-observed region inside a hollow organ of a patient, the not-yet-observed region being specified on the basis of an image that has been captured by an imaging sensor of an endoscope inside the hollow organ, and spatial disposition information of a distal end of an insertion part of the endoscope.

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.