Provided is a cell image analysis method which enables accurate grasping of a change point of a colony in cell culture. The cell image analysis method includes: a data acquisition step of acquiring cell image data generated in time series in the cell culture; a cell region extraction step of extracting cell regions from the cell image data; a data calculation step of calculating, for each of the cell regions, data about a size of the cell region; and a change point detection step of detecting, based on the data about the size of the cell region calculated in the data calculation step, the change point, which is timing of a change in a state of the colony.

This disclosure relates to diagnostic imaging of a retina of a patient with diabetic retinopathy. A processor retrieves a first image of the retina captured at a first point in time and a second image of the retina captured at a second point in time after the first point in time. The processor aligns the first image to the second image to reduce an offset between non-pathologic retina features in the first image and the second image and obtains image objects related to diabetic retinopathy in the first image and the second image. The processor then calculates a numerical pathology score indicative of a progression of the diabetic retinopathy by calculating a degree of change of the image objects related to diabetic retinopathy between the aligned first and second images and finally, creates an output representing the calculated numerical pathology score.

Provided is a system and method for estimating the motion of a target inside a tissue based on surface deformation of the soft tissue. The system consists of an acquisition unit, a reference input unit, two surface extraction units, a target position extraction unit, a feature calculation unit, and a target motion estimation unit. The method includes: the acquisition unit acquires an image I.sub.i of the soft tissue; the surface extraction unit extracts a surface f.sub.i of the soft tissue from I.sub.i; the reference input unit acquires a reference image I.sub.ref of the soft tissue; the surface extraction unit and the target position extraction unit respectively extract a reference surface f.sub.ref of the soft tissue and a target reference position t.sub.ref from I.sub.ref, the feature calculation unit calculates deformation feature Ψ.sub.i of f.sub.i relative to f.sub.ref, the target motion estimation unit estimates the target displacement based on Ψ.sub.i and t.sub.ref.

Methods and systems for analyzing a field. The methods and systems acquire a thermal image indicative of thermal energy emitted by the soil and/or plants in the field and process the thermal image to assess variations in certain characteristics of the soil and/or plants.

The present disclosure provides a method for treating clinical or pre-clinical skin damage in a skin field of a subject, wherein the skin field has been allocated a skin cancerization field index (SCR) score of at least 1 as determined by a process comprising the steps of: (i) assessing the number of keratoses in the skin field; (ii) assessing the thickness of the thickest keratosis in the skin field; and (iii) assessing the proportion of the field affected by clinical or subclinical skin damage. Based on the assessments made in (i), (ii) and (iii) the subject is optionally treated by at least one of (a) freezing one or more lesions, (b) shaving, curetting or surgically removing one or more lesions, (c) applying a topical treatment for actinic keratosis, basal cell carcinoma or squamous cell carcinoma, and (d) radiation therapy.

Method and systems are provided for characterizing blood flow in an atrioventricular valve of the human heart, the atrioventricular valve connecting an atrium with a corresponding ventricle of the heart, the ventricle being fluidly coupled to a particular vessel that transports blood outside the ventricle blood, which involve obtaining image data of the heart and identifying contours of the atrium and a region within the particular vessel within the image data. A time-density curve for the atrium can be calculated from the contour of the atrium and densitometric image data derived from the image data. A time-density curve for the region of the particular vessel can be calculated from the contour of the vessel region and the densitometric image data. Data that characterizes at least one regurgitation fraction related to the atrioventricular valve can be calculated from such time-density curves.

A tumor tracking system and method which leverages an image generator and an MD6DM model for tracking and monitoring a status of a tumor over time. In particular, the tumor tracking system enables a physician, or a group of physicians, in collaboration, to visualize and interact with an integrated representation of data relating to a patient's tumor and associated treatment history and also to plan future treatments of the tumor. An integrated and interactive tumor board generated by the tumor tracking system provides a single interface that compiles and organizes information from multiple sources to enable efficient tumor tracking and treatment planning.

Systems and methods for tracking eye movement during a diagnostic procedure include an eye tracker capturing images of an eye, and a control processor configured to detect an eye position and orientation in each of the images, determine an eye fixation position and orientation relative to an optical axis of the eye tracker, estimate eye fixation parameters based at least in part on the determined eye fixation position and orientation, and track the eye position and orientation by analyzing the images to determine the eye position and orientation relative to the eye fixation parameters. The eye fixation parameters may comprise a reference position and orientation of the eye when fixated. A histogram is constructed of detected eye positions and orientations and analyzed to determine an eye fixation position and orientation.

A method may include acquiring MR signals by an MR scanner and generating image data in a k-space according to the MR signals. The method may also include classifying the image data into a plurality of phases. Each of the plurality of phases may have a first count of spokes. A spoke may be defined by a trajectory for filling the k-space. The method may also include classifying the plurality of phases of the image data into a plurality of groups and determining reference images based on the plurality of groups. Each of the reference images may correspond to the at least one of the phases of the image data. The method may further include reconstructing an image sequence based on the reference images and the plurality of phases of the image data.

A method for processing images of lungs, the method comprising defining an inhale region of interest of the lungs at an inhale position and an exhale region of interest of the lungs at an exhale position, determining a spatial transformation of each voxel within the lungs between the lungs at the inhale position and the lungs at the exhale position to provide displacement vector estimates for each voxel within the lungs, and performing volume change inference operations to determine a volume change between the lungs at the inhale position and the lungs at the exhale position based on the inhale region of interest, the exhale region of interest, and the displacement vector estimates for each voxel within the lungs.