A method for acquiring at least one two-dimensional image of a part of arches of a patient includes steps carried out by the patient or other person who is not a dental health professional, for example, including placing a dental separator in the mouth of the patient in order to separate the lips of the patient and improve the visibility of the teeth during the acquisition of said at least one two-dimensional image, and acquiring, in a mouth closed position and with a personal image acquisition apparatus, said at least one two-dimensional image.

The present disclosure is directed to systems and methods for measuring and analyzing pupillary psychosensory responses. An electronic device is configured to receive video data with at least two frames. The electronic device then locates one or more eye objects in the video data and determine pupil and iris sizes of the one or more eye objects. The electronic device determines the pupillary psychosensory responses of the one or more eye objects by tracking a ratio of pupil diameter to iris diameter throughout the video. Several metrics for the pupillary psychosensory responses can be determined (e.g., velocity of change of the ratio, peak to peak amplitude of the change in ratio over time, etc.). These metrics can be used as measures of an individual's cognitive ability and mental health in a single session or tracked throughout multiple sessions.

Deep learning methods and systems for detecting biomarkers within optical coherence tomography volumes using such deep learning methods and systems are provided. Embodiments predict the presence or absence of clinically useful biomarkers in OCT images using deep neural networks. The lack of available training data for canonical deep learning approaches is overcome in embodiments by leveraging a large external dataset consisting of foveal scans using transfer learning. Embodiments represent the three-dimensional OCT volume by “tiling” each slice into a single two dimensional image, and adding an additional component to encourage the network to consider local spatial structure. Methods and systems, according to embodiments are able to identify the presence or absence of AMD-related biomarkers on par with clinicians. Beyond identifying biomarkers, additional models could be trained, according to embodiments, to predict the progression of these biomarkers over time.

A method of analyzing thoracic insufficiency syndrome (TIS) in a subject by performing quantitative dynamic magnetic resonance imaging (QdMRI) analysis. The QdMRI analysis includes performing four-dimensional (4D) image construction of a TIS subject's thoracic cavity. The 4D image includes a sequence of two dimensional (2D) images of the TIS subject's thoracic cavity over a respiratory cycle of the TIS subject. The QdMRI analysis also includes segmenting a region of interest (ROI) within the 4D image, determining TIS measurements within the ROI, comparing the TIS measurements to normal measurements determined from ROIs in 4D images of the thoracic cavities of normal subjects that are not afflicted by TIS, and outputting quantitative markers indicating deviation of the thoracic cavity of the TIS subject relative to the thoracic cavities of the normal subjects.

A system and method for generating a fusion of volumetric images and surface scan images said system comprising: a processor configuring the system to: receive both a volumetric image tooth mesh and surface scan image tooth crown mesh from a same patient, registered to a similar coordinate system; segment by anatomical structure each of the registered meshes that are in common between each of the registered volumetric image tooth mesh and the surface scan tooth crown mesh; and recognize a fusion vertices for each of the segmented volumetric image tooth mesh and segmented surface scan tooth crown mesh for matching the recognized meshes; remove a surface fragment from the matched volumetric image mesh in common with the matched surface scan image mesh for removal from the volumetric image mesh; and fuse the meshes by triangulating the recognized fusion vertices.

Computer implemented method of generating a dental design, comprising: (a) capturing a facial image comprising a head of a patient and a smile; (b) displaying it as a first image; (c) capturing a 3D intraoral scan; (d) aligning the 3D scan to the head; (e) determining bounding boxes in the 3D scan, each comprising a single tooth; (f) showing a view of the 3D scan and the bounding boxes as a second image; (g) showing the bounding boxes as overlay on the first image; (i) allowing the bounding boxes to be resized/repositioned; (ii) defining a limited set of parameters to characterize the tooth inside the bounding box, and searching a number of candidate matching teeth from a 3D digital library of teeth, and proposing a candidate matching tooth; (iii) overlaying the first image with a digital representation of the proposed candidate matching tooth from the digital library.

The dental bridge fitting system is a medical device. The dental bridge fitting system is configured for use in measuring the oral surface contours of a patient. The measurements taken by the dental bridge fitting system allow for the fabrication of a dental prosthetic device, such as a bridge, that fits flush on the oral surface that was measured by the dental bridge fitting system. The dental bridge fitting system comprises a mouthpiece, a plurality of capture devices, an image processor, and a master processor. The mouthpiece contains the plurality of capture devices. The plurality of capture devices, the image processor, and the master processor are electrically interconnected.

Several embodiments and methods are described for draining a lymphatic system for therapeutic purposes. The lymphatic draining can be performed by removal of fluid from the lymphatic system via a needle, a catheter, an access port, a reservoir, a shunt, or a combination of these devices. The drainage devices can be configured for use during only a single procedure or for reoccurring procedures.

The present invention relates to a device (100) for determining a vital sign of a subject by use of PPG. The device comprises a processing unit (110) configured to obtain multiple first detection signals derived from electromagnetic radiation (90) from multiple measurement spots (30) on a skin region (12) of the subject illuminated by one or more illumination spots (20), wherein the electromagnetic radiation (90) enters the skin region (12) at the one or more illumination spots (20) and exits the skin region (12) at the multiple measurement spots (30). The processing unit (110) further obtains 3D image information (130) of the skin region (12) which allows determining the actual spot distance (15) between the measurements spots (30) and an illumination spot (20), respectively. This information can be used to interpret the PPG signal more precisely as without having the 3D image information only a projected distance can be determined if the skin surface is tilted. Additionally, this allows averaging PPG signals derived from a homogenous skin area to improve PPG signal strength and reduce noise. A system (500) comprising such a device and a corresponding method are further described.

The present invention relates to a deep learning-based multiple skin lesion detection system, a multiple lesion detection method, and a computer-readable recording medium that has a program for implementing same recorded thereon. The system according to the present invention enables accurate classification and detection of various skin lesions having similar characteristics, on the basis of a context-dependent decision-making structure in which the local spatial correlation between various skin lesions in skin is considered.