Methods, apparatuses, and systems for automated disease detection using multiple-wavelength imaging are disclosed. The disclosed system uses multiple imaging modalities for assessing a medical condition. Data collected from multiple cameras and imaging modalities is processed to identify common structures. The common structures are used to scale and align images, which are analyzed to detect one or more medical conditions. Each acquired image is assessed, and the resulting probabilities are consolidated. The images can be assessed together by using artificial intelligence and machine learning.

A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image source into the proximal ends of the first optical fibers, wherein the first optical coupler comprises a plurality of lens elements including a first lens element and a second lens element, each of the plurality of lens elements comprising a primary surface facing a distal end of the first optical coupler, and a secondary surface facing a proximal end of the first optical coupler.

The present invention relates to a fitting room mirror including image capturing means and image processing means enabling the determination of body dimensions and in providing cloth-fitting advice to the user.

Presented are systems and methods for the accurate acquisition of medical measurement data of a body part of patient. To assist in acquiring accurate medical measurement data, an automated diagnostic and treatment system provides instructions to the patient to allow the patient to precisely position a medical instrument in proximity to a target spot of a body part of patient. Based on a series of images acquired from a kiosk camera and an instrument camera, these instructions are generated. Subsequent images from instrument camera are analyzed by automated diagnostic and treatment system utilizing a database and deep convolution neural network (DCNN) to obtain measured medical data. An error threshold measurement by the automated diagnostic and treatment system may determine the accuracy of the instrument positioning and the medical measured data. The measured medical data may be communicated to a physician.

A bed exit detection device (100) according to an embodiment of the present invention is mounted to a privacy rail (11) provided in the vicinity of a bed (10) to be monitored. The device (100) comprises a thermographic sensor (130) and a range sensor (40). The thermographic sensor comprises an array of sensing elements operable to generate an output value matrix from the output signals of each individual sensing element. The device (100) is also provided with a processing unit (150) operable to process the output value matrix of the thermographic sensor (130) and the distance output by the range sensor (140) so as to determine the position of a bed occupant and thereby (10) determine the likelihood of a bed exit event.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for location tracking. In some implementations, a corresponding method includes obtaining images of one or more persons within a property; identifying a heartbeat for each person of the one or more persons within the images; identifying a location for each person within the images; receiving a request that indicates a heartbeat signature generated from heartbeats sensed by a device worn by a user; determining that an identified heartbeat of a person of the one or more persons matches the heartbeat signature; in response to determining that the identified heartbeat of the person of the one or more persons matches the heartbeat signature, selecting the person as the user; and in response to selecting the person as the user, providing a response to the request based on a location of the person.

The present disclosure relates to systems and methods for positioning a subject. The method may include generating a first image of the subject disposed on a scanning board of an imaging device. The first image may include position information of the subject. The method may further include generating a second image of the subject which includes information associated with one or more organs of the subjects. Additionally, the method may include determining the position of a ROI based on the first image and the second image. The method may further include operating the imaging device to scan a target portion of the subject.

What is disclosed is an apparatus for enabling privacy for patients undergoing breast cancer screening in a non-clinical setting. One embodiment of the present apparatus comprises an enclosure in which a person can remove one or more garments to expose their breasts to a thermal camera for breast cancer screening. The enclosure is such that at least the breast area of that person is shielded from view by third parties. The apparatus also comprises a thermal camera for capturing thermal images of the exposed breast area. The thermal camera is connected to a robotic arm that changes the camera angle relative to real-world coordinates so that thermal images can be taken of the breast area from any angle between a frontal view and a left/right lateral view. A processor which executes a software interface tool for semi-automated or automated breast cancer screening based on the thermal images of the breast.

The present disclosure relates to systems and methods for positioning a subject. The method may include generating a first image of the subject disposed on a scanning board of an imaging device. The first image may include position information of the subject. The method may further include generating a second image of the subject which includes information associated with one or more organs of the subjects. Additionally, the method may include determining the position of a ROI based on the first image and the second image. The method may further include operating the imaging device to scan a target portion of the subject.

A method for creating a virtual patient model includes acquiring image data of the patient from a number of directions and in a number of positions of the patient. A virtual patient is created based upon the acquired image data. The virtual patient is adjusted to a posture of the patient during a planned examination with a medical engineering examination apparatus. A patient model creation apparatus is also described. Moreover, a medical engineering examination system is described.