Techniques for remote monitoring of a patient and corresponding medical device(s) are described. The remote monitoring comprises identifying a first set of images that represent a particular location of a body of a patient in which at least one component of an implantable medical device (IMD) coincides, determining a projection of alteration characteristics of the particular location of the body, identifying a second set of images, determining a second set of alteration characteristics, comparing the second set of alteration characteristics to the projection, and identifying a potential abnormality at the particular location of the body.

Methods and apparatus are disclosed that assist a user such as a doctor in examining large areas of skin quickly and effectively by determining an attribute associated with each of a plurality of skin features included in one or more images of skin; generating a tile image of each of the plurality of skin features; arranging the tile images in accordance with the attribute associated with each of the plurality of skin features; and controlling a display device to display the tile images of the plurality of skin features. Advantageously, systems and methods according to the present disclosure enable the organization and presentation of large sets of visual as well as non-visual data that can be readily navigated and assimilated by the user.

A system and method of displaying of multiple simultaneous views of a same region of a biological tissue sample. Logical instructions are executed by a processor to perform operations such as receiving a plurality of images of the biological tissue sample, converting the plurality of images to a common reference frame based on the individual metadata of each image, and arranging the plurality of images into a display pattern for simultaneous viewing of different aspects of the imaged biological tissue sample on a display screen. The plurality of images is produced by preprocessing images of the biological tissue sample. Each image shows a view mode of a same region of the biological tissue sample, and each image contains metadata that describe spatial orientation, such as the translation, rotation, and magnification, of the image to bring the plurality of images to a common view.

A method includes receiving a time series of slice images of medical imaging. The images have a region of interest located at a lung lesion. The method also includes tracking over at least one subset of slice images in a time series of slice images variations over time of at least one image parameter at the set of points in the region of interest. Classifier processing is applied to set of signals indicative of tracked time variations of the at least one image parameter at respective points in the set of points. A classification signal is indicative of the tracked time variations of the at least one image parameter reaching or failing to reach at least one classification threshold.

A system and method for image-based monitoring of an object inserted into a patient is disclosed. A model can be trained for an object configured to be inserted into a patient as part of a medical procedure, the trained model being generated from one or more machine learning algorithms that are trained on annotated images of the object with spatial information of the object. An imaging computer system can receive one or more images of the object inserted within the patient captured by an imaging device positioned external to the patient. The imaging computer system can further determine, based on applying the trained model to the one or more images of the object, current spatial information of the object within the patient. A display can output the one or more images and the current spatial information of the object.

A medical image-processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a first medical image captured at first timing, and a second medical image in which an identical position to the first medical image is captured at second timing, which is different from the first timing, identifies a change region to be a logical OR of a first region included in the first medical image and a second region that corresponds to the first region and is included in the second medical image when the first medical image and the second medical image are overlaid on each other in an aligned manner, and calculates a degree of change of the change region between the first timing and the second timing based on the first region and the second region that form the change region.

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.

Methods for characterizing fluids from a patient. A time series of images of a conduit are received, and a conduit image region in the images is identified. A flow type of the fluids passing through the conduit may be classified as one of air, laminar liquid, and turbulent liquid by evaluating an air-liquid boundary of the fluid. A volumetric flow rate of the fluids in the conduit is estimated. The volumetric flow rate may be based on the classified flow type. A concentration of a blood component of the fluids passing through the conduit may be estimated based on the images. A proportion of the fluid that is blood may also be determined, and a volume of blood that has passed through the conduit within a predetermined period of time may be estimated based on the estimated total volumetric flow rate and the determined proportion.

The invention relates to systems and methods for predicting ischemic brain tissue fate from multi-phase CT-angiography. More specifically, systems and methods are provided that enable meaningful prediction of core, penumbra and perfusion from mCTA images using software that has been trained via machine learning to interpret mCTA images.

Disclosed herein are platforms, systems, and methods including a cell culture system that includes a cell culture container comprising a cell culture, the cell culture receiving input cells, a cell imaging subsystem configured to acquire images of the cell culture, a computing subsystem configured to perform a cell culture process on the cell culture according to the images acquired by the cell imaging subsystem, and a cell editing subsystem configured to edit the cell culture to produce output cell products according to the cell culture process.