A 3-D imaging system including a computer determining a plurality of coherence factors measuring an intensity contrast between a first intensity of a first region of an interference comprising constructive interference between a sample wavefront and a reference wavefront, and a second intensity of a second region of the interference comprising destructive interference between the sample wavefront and the reference wavefront, wherein the interference between a reference wavefront and a reflection from different locations on a surface of an object. From the coherence factors, the computer determines height data comprising heights of the surface with respect to an x-y plane perpendicular to the heights and as a function of the locations in the x-y plane. The height data is useful for generating a three dimensional topological image of the surface.

In an aspect for generating device-specific OCT image, one or more processors may be configured for receiving, at a unified domain generator, first image data corresponding to OCT image scans captured by one or more OCT devices; processing, by the unified domain generator, the first image data to generate second image data corresponding to a unified representation of the OCT image scans; determining by a unified discriminator, third image data corresponding to a quality subset of the unified representation of the OCT image scans having a base resolution satisfying a first condition and a base noise type satisfying a second condition; and processing, using a conditional generator, the third image data to generate fourth image data corresponding to device-specific OCT image scans having a device-specific resolution satisfying a third condition and a device-specific noise type satisfying a fourth condition.

The present disclosure relates to a method and a system of quantitative intravascular optical coherence tomography. The method includes: acquiring and graying an intravascular optical coherence tomography cross-sectional image, and converting it into a polar coordinate view; calculating a confocal function value and a sensitivity function value according to parameters of the imaging system; establishing a model of an intensity of a backscattered signal being attenuated depending on the detection depth, according to the confocal function value and the sensitivity function value to obtain a theoretical value of the backscattered signal; determining a measured value of the backscattered signal; constructing an error function according to the theoretical value and the corresponding measured value; minimizing the error function to determine a light attenuation coefficient corresponding to each polar coordinate; and determining a spatial distribution diagram of the light attenuation coefficient according to the light attenuation coefficient corresponding to each polar coordinate.

In an aspect for generating device-specific OCT image, one or more processors may be configured for receiving, at a unified domain generator, first image data corresponding to OCT image scans captured by one or more OCT devices; processing, by the unified domain generator, the first image data to generate second image data corresponding to a unified representation of the OCT image scans; determining by a unified discriminator, third image data corresponding to a quality subset of the unified representation of the OCT image scans having a base resolution satisfying a first condition and a base noise type satisfying a second condition; and processing, using a conditional generator, the third image data to generate fourth image data corresponding to device-specific OCT image scans having a device-specific resolution satisfying a third condition and a device-specific noise type satisfying a fourth condition.

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.

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.

Disclosed herein are methods and systems for automated detection of shadow artifacts in optical coherence tomography (OCT) and/or OCT angiography (OCTA). The shadow detection includes applying a machine-learning algorithm to the OCT dataset and the OCTA dataset to detect one or more shadow artifacts in the sample. The machine-learning algorithm is trained with first training data from first training samples that include manufactured shadows and no perfusion defects and second training data from second training samples that include perfusion defects and no manufactured shadows. The shadow artifacts in the OCTA dataset and/or OCT dataset may be suppressed to generate a shadow-suppressed OCTA dataset and/or a shadow-suppressed OCT dataset, respectively. Other embodiments may be described and claimed.

Presented herein are systems and methods for tomographic imaging of a region of interest in a subject using short-wave infrared light to provide for accurate reconstruction of absorption maps within the region of interest. The reconstructed absorption maps are representations of the spatial variation in tissue absorption within the region of interest. The reconstructed absorption maps can themselves be used to analyze anatomical properties and biological processes within the region of interest, and/or be used as input information about anatomical properties in order to facilitate data processing used to obtain images of the region of interest via other imaging modalities. For example, the reconstructed absorption maps may be incorporated into forward models that are used in tomographic reconstruction processing in fluorescence and other contrast-based tomographic imaging modalities. Incorporating reconstructed absorption maps into other tomographic reconstruction processing algorithms in this manner improves the accuracy of the resultant reconstructions.

An image processing apparatus includes: an obtaining unit configured to obtain a first medical image of an object under examination; an image quality improving unit configured to generate, from the obtained first medical image, a second medical image with image quality higher than image quality of the obtained first medical image using a learned model; a comparing unit configured to compare an analysis result obtained by analyzing the obtained first medical image and an analysis result obtained by analyzing the generated second medical image; and a display controlling unit configured to cause a comparison result obtained by the comparing unit to be displayed on a display unit.

A system for non-contact imaging of corneal tissue stored in a viewing chamber using Gabor-domain optical coherence microscopy (GDOCM), wherein a 3D numerical flattening procedure is applied to the image data to produce an at least substantially artifact-free en face view of the endothelium.