Systems and methods are provided in which intraoperatively acquired surface data is employed to verify the correspondence of an intraoperatively selected spinal level with a spinal level that is pre-selected based on volumetric image data. Segmented surface data corresponding to the pre-selected spinal levels may be obtained from the volumetric image data, such that the segmented surface data corresponds to a spinal segment that is expected to be exposed and identified intraoperatively during the surgical procedure. The segmented surface data from the pre-selected spinal level, and adjacent segmented surface data from an adjacent spinal level that is adjacent to the pre-selected spinal level, is registered to the intraoperative surface data, and quality measures associated with the registration are obtained, thereby permitting an assessment or a determination of whether or not the pre-selected spinal surface (in the volumetric frame or reference) is likely to correspond to the intraoperatively selected spinal level.

In various embodiments, a method for determining a homogeneity of complexion is provided. The method may include provision of a digital image on which skin is portrayed and which is parameterized in a color space which is defined by a parameter set in which one of the parameters is a hue, identifying and/or defining at least one skin examination area in the transformed image, calculating a hue distribution in the at least one skin examination area, and determining at least one homogeneity value for the complexion based on the calculated hue distribution.

Some embodiments of the present disclosure provide a pneumothorax detection method performed by a computing device. The method may comprise obtaining predicted pneumothorax information, predicted tube information, and a predicted spinal baseline with respect to an input image from a trained pneumothorax prediction model; determining at least one pneumothorax representative position for the predicted pneumothorax information and at least one tube representative position for the predicted tube information, in a prediction image in which the predicted pneumothorax information and the predicted tube information are displayed; dividing the prediction image into a first region and a second region by the predicted spinal baseline; and determining a region in which the at least one pneumothorax representative position and the at least one tube representative position exist among the first region and the second region.

In an embodiment, a method (100) is described. The method comprises obtaining (102) a three-dimensional representation of a body surface. The method further comprises obtaining illumination information for the three-dimensional representation that is indicative of an orientation of the body surface relative to a reference axis. The method further comprises determining illumination compensation information (104). The illumination compensation information is used (106) to compensate for an illumination variation apparent from the illumination information in an image of the body surface.

A computer program and computer-based system for remotely determining a dental treatment plan (10) of a user (30) of a personal computing device (20) by obtaining, using the personal computing device (20), at least one digital image (1) of the person’s oral cavity (31) and additional non-image data (2) comprising a choice (7) of a predefined topic (5) by said user (30). The digital images (1) and non-image data (2) are processed to extract dental health indicators (8) that are used to evaluate any dental condition (9) of said user (30). A dental treatment plan (10) is generated based on the dental condition (9) and a database (3) defining logical relationships between predefined topics (5) and actions (6) for said user (30) to take, wherein a selection of said actions (6) arranged in a regimen and displayed on a user interface (25) of said personal computing device (20).

A system for and a method of analyzing a corneal lesion using an anterior segment image according to the present invention. The system includes: an image acquisition unit configured to acquire an anterior segment image from the eyeball of a subject, a feature extractor configured to extract feature information on a position and a cause of a lesion in the cornea from the anterior segment image by applying a convolution layer to the anterior segment image through machine learning on the basis of a database in which clinical information pre-acquired by analyzing positions and causes of lesions in the corneas of subjects is stored; and a result determination unit configured to identify a position of the cornea from the anterior segment image using the feature information and to analyze and determine the position and the cause of the lesion in the cornea from the position of the cornea.

An electronic endoscope system includes a plotting unit which plots pixel correspondence points, which correspond to pixels that constitute a color image that has multiple color components, on a first color plane according to color components of the pixel correspondence points, the first color plane intersecting the origin of a predetermined color space; an axis setting unit which sets a predetermined reference axis in the first color plane; a transform unit which defines a second color plane that includes the reference axis, and subjecting the pixel correspondence points on the first color plane to projective transformation onto the second color plane; and an evaluation value calculating unit which calculates a prescribed evaluation value with respect to the color image based on the pixel correspondence points subjected to projective transformation onto the second color plane.

The present disclosure provides systems and methods for diagnosing disease. In some aspects, an imaging system is provided that includes a light source configured to illuminate a retina of the eye with light, one or more imaging devices configured to receive light returned from the retina to generate one or more spatial-spectral images of the retina, and a computing device configured to receive the one or more spatial-spectral images of the retina, evaluate the one or more spatial-spectral images, and identify one or more biomarkers indicative of a neurogenerative pathology.

A healthcare apparatus includes a ballistocardiogram (BCG) sensor configured to sense a ballistocardiogram signal of a subject, a camera configured to acquire a color facial image, and a processor configured to detect a region of interest (ROI) from the color facial image, to detect a first color image of a forehead area to acquire a first black and white image, to detect a second color image of a cheek area to acquire a second black and white image, to apply the first and second black and white images to a predetermined trained algorithm model to output a remote photoplethysmography (rPPG) signal waveform of the subject, to calculate a first heart rate from the BCG signal waveform, to calculate a second heart rate from the remote PPG signal waveform, and to output a heart rate of the subject based on the first heart rate and the second heart rate.

A catheter for diagnosing an abnormality of a blood vessel includes an elongated body defining an elongated lumen therethrough; and one or more transducers disposed on an outer surface of the elongated body. One or more transducers are configured to output an electrical signal in response to sound.