Hoya Corporation

Toshio Tachibana

Tadashi Minakuchi

Noriko Ota

Yousuke Ikemoto

Atsushi Komoro

Yoichi Hitokata

A processor for an endoscope or the like that assists an endoscopic examination using an appropriate reference image is provided. A processor for an endoscope includes an image acquisition unit that acquires an endoscope image; a region acquisition unit that inputs the endoscope image acquired by the image acquisition unit to a first learning model that outputs a target region corresponding to a predetermined region to be photographed when the endoscope image is input to acquire the target region; and an image output unit that outputs the endoscope image acquired by the image acquisition unit and an index indicating the target region acquired by the region acquisition unit with the endoscope image and the index superimposed.

Endoscope processor, training device, information processing method, training method and program

To provide an endoscope processor () and the like that can output the aggregation results of lesions for each examination part. The endoscope processor () according to one aspect includes an image acquisition unit that acquires a captured image from a large-intestine endoscope (), a part identification unit that identifies a part in a large intestine based on the captured image acquired by the image acquisition unit, a polyp extraction unit that extracts a polyp from the captured image, an aggregation unit that aggregates the number of polyps for each part identified by the part identification unit, and an output unit that outputs an endoscope image based on the captured image and an aggregation result aggregated by the aggregation unit.

Endoscope processor, information processing device, and endoscope system

An image processing apparatus has an image data obtaining means configured to obtain image data acquired by photographing biological tissue, a score calculating means configured to calculate a score representing severity degree of lesion of the biological tissue photographed in an image represented by the image data for each pixel based on the image data, a reliability evaluation means configured to evaluate reliability of the score based on the image data, and a score reliability calculating means configured to calculate score reliability which represents a ratio of pixels of which scores having predetermined reliability to all the pixels of the image data.

Image processing apparatus

Provided is a correction data generation method that includes acquiring captured image data by imaging an indicator that is related to a predetermined illness; plotting a real imaging data point that corresponds to the acquired captured image data in a predetermined color space that is associated with the predetermined illness in accordance with a color component of the data point; calculating a correction value for correcting the values of pixels that make up a captured image captured by an electronic endoscope based on the distance between the data point and a predetermined target point in the predetermined color space; and storing the calculated correction value.

Correction data generation method and correction data generation apparatus

An image processing apparatus has a color image obtaining means configured obtain color image data representing a color image of biographic tissues, a lesion determining means configured to determine whether each pixel of the color image is of a lesion part based on the color image data, and a marking means configured to apply a mark indicating a position of the lesion part on the color image based on a result of determination, and the mark is configured such that the color image at a background of the mark can be seen.

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Tokyo, Japan

Toshio Tachibana