A bioanalysis system includes: an acquisition unit that obtains a plurality of two-dimensional data with different depths in a skin of a living body; a position identification unit that identifies a position of a pore part in the skin of the living body from at least one of the plurality of two-dimensional data; an extraction unit that extracts a diameter of the pore part from each of the plurality of two-dimensional data; and a type identification unit that identifies a type of the pore part, on the basis of the diameter of the pore part. According to such a bioanalysis system, it is possible to properly identify the position and the type of the pore part in the skin of the living body.

A medical diagnostic apparatus includes a receiver circuit that receives three-dimensional data of an eye, and processing circuitry configured to segment the three-dimensional data into regions that include a target structural element and regions that do not include the target structural element to produce a segmented three-dimensional data set. The segmenting is performed using a plurality of segmentation algorithms. Each of the plurality of segmentation algorithms is trained separately on different two-dimensional data extracted from the three-dimensional data. The processing circuitry is further configured to generate at least one metric from the segmented three-dimensional data set, and evaluate a medical condition based on the at least one metric.

Provided is a processing apparatus capable of obtaining a 2D image from 3D tomographic images, extracting an image for accurate authentication, and extracting an image at a high speed. A processing apparatus includes: means for calculating, from three-dimensional luminance data indicating an authentication target, depth dependence of striped pattern sharpness in a plurality of regions on a plane perpendicular to a depth direction of the target; means for calculating a depth at which the striped pattern sharpness is the greatest in the depth dependence of striped pattern sharpness; rough adjustment means for correcting the calculated depth on the basis of depths of other regions positioned respectively around the plurality of regions; fine adjustment means for selecting a depth closest to the corrected depth and at which the striped pattern sharpness is at an extreme; and means for extracting an image with a luminance on the basis of the selected depth.

Provided herein is technology relating to analysis of images and particularly, but not exclusively, to methods and systems for determining the area and/or volume of a region of interest using optical coherence tomography data. Some embodiments provide for determining the area and/or volume of a lesion in retinal tissue using three-dimensional optical coherence tomography data and a two-dimensional optical coherence tomography fundus image.

Disclosed is a method (100) for correcting artifacts in Optical Coherence Tomography (OCT) images. The method involves acquiring an OCT image and subsequently transforming it from a Cartesian coordinate system to a polar coordinate system via polar reconstruction, generating a reconstructed polar OCT image. This image is then segmented into RED, GREEN, BLUE color channels. Fourier transformation is applied to each channel, transitioning them into their frequency domain representations. A custom frequency mask is utilized on these images, filtering out artifact-related frequencies. Following this, an inverse Fourier transformation is executed, reverting the images back to their Cartesian format. These images are then combined to produce a reconstituted OCT image. Further, this reconstituted image is merged with the original OCT image, resulting in an OCT image that is substantially free from artifacts.

Disclosed is a method for phase-restoring translational shifting of a multidimensional image. The method comprises computing a first shifted, complex-valued image by converting a spectral signal (corresponding to the multidimensional image) to a shifted spectral signal and transforming the shifted spectral signal along a first axis. A spatial frequency component of the multidimensional image is then computed by transforming the first shifted, complex-valued image along at least one further axis perpendicular to the first axis. Thereafter, a phase-restored image is produced by converting the spatial frequency component of the multidimensional image to a shifted spatial frequency spectrum and applying an inverse transform in each second axis. Also disclosed is a system for performing the above method.

An image generation apparatus includes an image acquisition unit and an outputting unit. The image acquisition unit acquires a medical image. Based on the medical image acquired by the image acquisition unit, the outputting unit outputs a contrast effect image that depicts a contrast effect corresponding to contrast time that includes contrast time moment that is at least one point in time.

A signal processing device includes a controller which acquires an output signal output from a single light receiver that receives a plurality of interference beams in which a light beam that is output from a single light source and traces a sample arm toward a measurement target and a light beam that is output from the light source and traces a reference arm that is different from the sample arm interfere with each other, the plurality of interference beams each having a different wavelength dispersion characteristic difference between the sample arm and the reference arm traced by the light beams interfering with each other; and extracts an extraction signal that is a signal for each of the interference beams on the basis of the output signal acquired and a correction signal obtained by applying wavelength dispersion correction processing to the output signal.