The present invention relates to an eye surgery method and an eye surgery system. An eye surgery method comprises directing illumination light direction onto a target object of an eye; generating an observation image from observation light emerging from the target object due to scattering of the illumination light at the target object; highlighting, in the observation image, a region of interest characterized by a specific wavelength range by modifying the observation light or by modifying digital raw image data representing a spatial intensity distribution of the observation light; and identifying the target object in the observation image including the highlighted region of interest and manipulating at least one part of the identified target object.

A device for analyzing and treating tonal imperfections on human skin. The device, or apparatus has an applicator comprising a head and one or more nozzles, preferably the nozzles are arranged in an array. The apparatus further has a reservoir comprising a skin treatment composition, a sensor, and a CPU. The sensor takes an image of at least 10 μm.sup.2 of skin. The CPU analyzes the image to calculate a localized L value of individual pixels or group of pixels. The CPU then compares the local L value to a background L value to identify one or more skin deviations, and wherein the sensor is in wireless communication with the CPU, and wherein the CPU is adjacent the sensor or is remotely located. Further, the sensor may be enclosed within an apparatus handle and the CPU is either within the handle or external to the handle. In another embodiment of this invention, there are two or more CPUs and the sensor can be in wireless communication with none, one or more than one CPU.

A method for determining MRI biomarkers for in vivo issue includes the steps of obtaining raw data concerning the in vivo tissue from a MRI machine; processing the raw data to obtain parameter maps; when applicable, registering images such that the exact same tissue at serial points can be analyzed; applying a grid over a region of interest to create sub-regions of interest (SROIs); inserting parameter measures for each SROI into a spreadsheet program to create a large 3D data matrix; applying standard big-data analytics including data mining and statistics of matrix measures to find patterns of measurement values or measure changes (which may include established biomarkers). A medical imaging software program is used to obtain the parameter maps from the raw data and place multiple grids over the SROIs. 3D matrix measures may be data mined and analyzed using standard big-data analytics.

There is provided a computer implemented method for detection of likelihood of malignancy in an anatomical image of a patient for treatment planning, comprising: receiving an anatomical image, feeding the anatomical image into a global component of a model trained to output a global classification label, feeding the anatomical image into a local component of the model trained to output a localized boundary, feeding the anatomical image patch-wise into a patch component of the model trained to output a patch level classification label, extracting a respective set of regions of interest (ROIs) from each one of the components, each ROI indicative of a region of the anatomical image likely to include an indication of malignancy, aggregating the ROIs from each one of the components into an aggregated set of ROIs, and feeding the aggregated set of ROIs into an output component that outputs an indication of likelihood of malignancy.

The present invention relates to the field of medical monitoring, and in particular non-contact video monitoring to measure tidal volume of a patient. Systems, methods, and computer readable media are described for determining a region of interest of a patient and monitoring that region of interest to determine tidal volume of the patient. This may be accomplished using a depth sensing camera to monitor a patient and determine how their chest and/or other body parts are moving as the patient breathes. This sensing of movement can be used to determine the tidal volume measurement.

An apparatus for estimating bio-information is provided. The apparatus for estimating bio-information may include: a pulse wave sensor configured to measure a pulse wave signal from an object; a force sensor configured to measure a force exerted by the object to the pulse wave sensor; and a processor configured to obtain a contact pressure based on the force and a reference contact area between the object and a contact surface, and estimate bio-information based on the contact pressure and the pulse wave signal.

The disclosure provides a method of and an imaging system for clinical sign detection. The method uses an imaging system having an RGB image sensor and the processing device disclosed herein. An image of a patient or examinee is captured by the RGB image sensor to generate an RGB image. Clinical signs of the patient or examinee are detected by the processing device based on the RGB images.

Described embodiments include a system that includes an electrical interface and a processor. The processor is configured to receive, via the electrical interface, an electrocardiographic signal from an electrode within a heart of a subject, to ascertain a location of the electrode in a coordinate system of a computerized model of a surface of the heart, to select portions of the model responsively to the ascertained location, such that the selected portions are interspersed with other, unselected portions of the model, and to display the model such that the selected portions, but not the unselected portions, are marked to indicate a property of the signal. Other embodiments are also described.

Aspects of the present invention relate to a method of detecting clipping of retinal image content in an optical coherence tomography, OCT, image of a patient’s retina. The method comprises detecting a boundary of the retinal image content in the OCT image and calculating a distance between the boundary and an edge of the OCT image. The method further comprises determining if clipping of the retinal image content in the OCT image has occurred by comparing the calculated distance between the boundary and the edge of the OCT image with a clipping threshold distance. Clipping of the retinal image content is determined to have occurred when the calculated distance between the boundary and the edge of the OCT image is equal to, or less than, the clipping threshold distance.

The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.