A method and system for detecting spinal stenosis is provided. The method may receive image data corresponding to a spine region of a patient. The method may also identify a spinal cord in the image data. The method may determine at least one compression of the spinal cord and may mark an anatomical element proximate to a location of the determined at least one compression to yield at least one marking. The method may generate a decompression plan based on the at least one marking.

The present invention relates to a method for producing complex reality three-dimensional images and a system for same, the method comprising: (a) a step for determining first reality three-dimensional spatial coordinates for a three-dimensional image of a human body; (b) a step for determining second reality three-dimensional spacial coordinates for an image of an item of medical equipment; (c) a step for obtaining a three-dimensional image of the area surrounding the medical equipment, from an imaging means in the medical equipment, and determining third reality three-dimensional spatial coordinates for said image; (d) a step for examining an image that is at the same coordinates in the three kinds of three-dimensional spatial coordinates; and (e) a step for producing a complex reality three-dimensional image by selecting the one image that is at the same coordinates, if there is one image at the same coordinates, or selecting the necessary image or images from among a plurality of images, if there are multiple images at the same coordinates.

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 computer-implemented method for automated classification of 3D image data of teeth includes a computer receiving one or more of 3D image data sets where a set defines an image volume of voxels representing 3D tooth structures within the image volume associated with a 3D coordinate system. The computer pre-processes each of the data sets and provides each of the pre-processed data sets to the input of a trained deep neural network. The neural network classifies each of the voxels within a 3D image data set on the basis of a plurality of candidate tooth labels of the dentition. Classifying a 3D image data set includes generating for at least part of the voxels of the data set a candidate tooth label activation value associated with a candidate tooth label defining the likelihood that the labelled data point represents a tooth type as indicated by the candidate tooth label.

To easily evaluate the performance of an earphone-type device used for otoacoustic authentication at low cost.

A generation unit (31) generates earhole shape data indicating the three-dimensional shape of an individual's ear canal, on the basis of data on the internal structure of an individual's earhole, a center line calculation unit (32) calculates the center line of the ear canal, on the basis of the ear canal shape data, and a dividing unit (33) divides the ear canal into a plurality of layers perpendicular to the center line, and calculates, for each of the divided layers, parameters indicating the shape of the ear canal.

An image processing device is an image processing device configured to cause a display to display three-dimensional data as a three-dimensional image, the three-dimensional data representing a biological tissue. The image processing device includes: a control unit configured to adjust a color tone of each pixel of the three-dimensional image according to a dimension of the biological tissue in a linear direction from a viewpoint when the three-dimensional image is displayed on the display.

An image processing device is an image processing device configured to cause a display to display, as a three-dimensional image, three-dimensional data representing a biological tissue having a longitudinal lumen. The image processing device includes: a control unit configured to calculate centroid positions of a plurality of cross sections in a lateral direction of the lumen of the biological tissue by using the three-dimensional data, set a pair of planes intersecting at a single line passing through the calculated centroid positions as cutting planes, and form, in the three-dimensional data, an opening exposing the lumen of the biological tissue from a region interposed between the cutting planes in the three-dimensional image.

An image processing device is an image processing device configured to cause a display to display three-dimensional data as a three-dimensional image, the three-dimensional data representing a biological tissue. The image processing device includes: a control unit configured to detect a series of positions of a catheter inserted into the biological tissue from data obtained in time series by a sensor observing the surrounding of a lumen of the biological tissue while moving in the lumen, and to switch a display mode between a first mode for displaying a first figure representing the series of positions in the three-dimensional image, and a second mode for displaying a second figure representing one position among the series of positions in the three-dimensional image.

An image processing apparatus includes at least one processor, and the processor derives three-dimensional coordinate information that defines a position of a structure in a tomographic plane from a tomographic image including the structure, and that defines a position of an end part of the structure outside the tomographic plane in a direction intersecting the tomographic image.

The present disclosure relates to an image processing method, a storage medium and a mapping system. An imageological image including a plurality of tomographic images is acquired. A three-dimensional reconstruction is performed according to the plurality of tomographic images to obtain a three-dimensional image model. The three-dimensional image model includes a three-dimensional myocardial fibrosis region image. A three-dimensional electroanatomic model including a three-dimensional abnormal myocardial tissue image is acquired. Since there is a certain correlation between an abnormal myocardial tissue region in the three-dimensional electroanatomic model and myocardial fibrosis, the three-dimensional image model and the three-dimensional electroanatomic model are registered, and an overlapping part of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image is determined as the location of a lesion. Therefore, the accurate positioning of a lesion location is realized, which effectively improves the surgery success rate.