A computer-implemented method of searching for a region indicative of a pathology in an image of a portion of an eye acquired by an ocular imaging system, the method comprising: receiving image data defining the image; searching for the region in the image by processing the received image data using a learning algorithm; and in case a region in the image that is indicative of the pathology is found: determining a location of the region in the image; generating an instruction for an eye measurement apparatus to perform a measurement on the portion of the eye to generate measurement data, using a reference point based on the determined location for setting a location of the measurement on the portion of the eye; and receiving the measurement data from the eye measurement apparatus.

Embodiments of the present disclosure are related to providing a method and device processing a first set of volumetric image data comprising cross-sectional images of a myocardium and displaying a second set of volumetric image data of the myocardium. A curved plane to rectangular plane transformation of cross-sectional images of myocardium of human heart is proposed. After the transformation, a combined and reconstructed set of myocardium images are superimposed with a modified Bull's Eye View (BEV) map and corresponding parameters indicating extent of fibrosis to obtain a second set of volumetric image data of myocardium. In addition to quantifying and displaying the extent of fibrosis, the proposed solution preserves neighborhood and adjacency criteria of abnormal tissues of myocardium walls of human heart.

The present invention provides method for monitoring physiological status of an organ in a subject by monitoring morphological changes over time in transplanted tissue on an eye of the subject.

Systems and methods for health and body simulations in order to predict numerous physiological parameters in a subject or a population of subjects based on the input of limited physiological data.

Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and/or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and/or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and/or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.

A system and method for preliminarily identifying a medical condition in a monitored patient. A predetermined set of patient physiological parameters that are indicative of the presence of a medical condition is monitored. If all of the patient physiological parameters meet a predetermined criteria, a notification is activated that is indicative of the presence of the medical condition. Optionally, users are provided with guidance concerning additional patient physiological parameters to be checked to confirm the presence of the medical condition.

Methods and systems for imaging and analysis are described. Accurate pressure ulcer measurement is critical in assessing the effectiveness of treatment. However, the traditional measuring process is subjective. Each health care provider may measure the same wound differently, especially related to the depth of the wound. Even the same health care provider may obtain inconsistent measurements when measuring the same wound at different times. Also, the measuring process requires frequent contact with the wound, which increases risk of contamination or infection and can be uncomfortable for the patient. The present application describes a new automatic pressure ulcer monitoring system (PrUMS), which uses a tablet connected to a 3D scanner, to provide an objective, consistent, non-contact measurement method. The present disclosure combines color segmentation on 2D images and 3D surface gradients to automatically segment the wound region for advanced wound measurements.

The present relates, in general terms, to a device for monitoring oxidative stress in a sample, a method of making the device and a method of monitoring oxidative stress in a sample thereof.

A method measures a perfusion wave upstroke associated with leg perfusion dynamics, the perfusion wave upstroke including two phases, an initial slow phase and a fast-rising phase, and using prolongation of the slow phase to detect a presence of arterial stenosis and to assess stenosis severity.

The present invention relates to a method and system for identifying treatable and remediable factors of Dementia and aging cognitive changes, to provide recommendations for aiding in the diagnosis of dementia or predementia symptoms in a subject. According to an embodiment of the invention, the method comprising: receiving data relative to medical history and examinations, processing said received data by applying an algorithm(s) relative to the Intensive Neuropsychogeriatric Evaluation, Treatment and Prevention (INETAP) method, and verifying whether said processed data is sufficient for indicating of advanced Dementia Potential Remediable Conditions (PRCs), and outputting data for aiding in the diagnosis of one of the following: dementia PRCs, pre-dementia PRCs, no dementia/pre-dementia, or Dementia without treatment horizon.