According to an embodiment of the present disclosure, there is provided a method of predicting a brain tissue lesion distribution, the method including: a model learning operation of learning a prediction model for predicting a brain tissue lesion distribution of a subject by using brain image data of a plurality of previous patients; an input obtaining operation of obtaining input data from brain image data of the subject; and an output operation of generating output image data including information on the lesion distribution after recanalization treatment for the subject, by using the prediction model. The prediction model includes a success prediction model that is learned by using data of patients in which recanalization treatment is successful among the plurality of previous patients, and a failure prediction model that is learned by using data of patients in which recanalization treatment fails among the plurality of previous patients.

The present method and system provides a neuromodulation therapy including receiving a plurality of input data relating to a patient, the input data including brain value measurements and body value measurements. The method and system includes analyzing the input data in reference to reference data generated based on machine learning operations associated with existing patient data and reference database data. Based thereon, the method and system includes electronically determining, a brain malady and a severity value for the patient and electronically generating a treatment protocol for the patient, the treatment protocol includes transcranial stimulation parameters. Therein, the method and system includes applying a transcranial stimulation using the transcranial stimulation parameters based on the treatment protocol.

Systems and methods for monitoring neuroplasticity within at least one region of interest of a brain of a subject are disclosed. The method includes transforming at least one time sequence of signals indicative of neural activity into a summary parameter indicative of plasticity pulses. The method further includes evaluating the summary parameter with respect to one or more threshold values to obtain a determination of neuroplasticity within at least one region of interest of the subject. The method may be used to evaluate the efficacy of a neuroactive therapy, such as a neuroactive medication, a physical therapy, an occupational therapy or a speech therapy. The summary parameter obtained using the disclosed method may be displayed to a subject as a biofeedback during a neurotherapy.

Treatment trajectory guidance systems and methods are provided. In one embodiment, the method for treatment trajectory guidance in a patient's brain includes obtaining a three- dimensional (3D) brain model that includes a model of an anatomy, the model of the anatomy including a plurality of feature points; modifying the 3D brain model based on magnetic resonance (MR) data of the patient's brain from a magnetic resonance imaging (MRI) device to obtain a plurality of modified feature points on a modified model of the patient's anatomy in the patient's brain; displaying on a display a first planned trajectory for treating the patient's anatomy based on the plurality of modified feature points; and displaying, on the display, a first estimated treatment result for the first planned trajectory.

We report method of detecting a pathological body state of a patient, comprising receiving a body signal of the patient; determining a body index from said body signal; determining an activity level of said patient; determining a value range for said body index for said patient, based at least in part on said activity level; comparing said body index to said value range; and detecting a pathological state when said body index is outside said value range. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

The invention relates to a method for the real-time monitoring and evaluation of the state of a patient with a neurological condition from the indicative parameters of the state of the patient obtained by means of an EEG, comprising a step of measuring the EEG by means of at least one sensor, a step of processing the measured values, a step of extracting at least one set of values of the indicative parameters of the state of the patient, each set of values being extracted from time segments of the EEG, a step of calculating for each time segment the risk level of the patient suffering a crisis due to the neurological condition, the risk level being calculated by applying at least one mathematical classification model to each corresponding set of values, and a step of classifying the state of the patient between at least an alert or preictal state and a non-alert or non-preictal state, depending on a threshold level.

An exemplary magnetic field measurement system includes a wearable sensor unit that includes a magnetometer and a twisted pair cable interface assembly electrically connected to the magnetometer.

DICOM data is automatically prepared for transit outside of the clinical-data infrastructure, by examining a plurality of metadata fields in the corresponding metadata in the DICOM data; identifying a first subset of the metadata fields as containing private information; identifying a second subset of the metadata fields as private-information free; accessing at least some of the plurality of layers of the DICOM data; and transforming the accessed layers into a single transmission-image, the transmission-image being in a format i) other than DICOM and ii) that stores the second subset of the metadata fields as transmission-metadata in a scheme that is non-redundant for a given transmission-image.

Systems and methods for high-resolution STAGE imaging can include acquisition of relatively low-resolution k-space datasets with two separate multi-echo GRE sequences. The multi-echo GRE sequences can correspond to separate and distinct flip angles. Various techniques for combining the low-resolution k-space datasets to generate a relatively high-resolution k-space are described. These techniques can involve combining low-resolution k-space datasets associated with various echo types. The STAGE imaging approaches described herein allow for rapid imaging, enhanced image resolution with relatively small or no increase in MR data acquisition time.

Systems and methods are provided for performing thermophotonic imaging using cross-correlation and subsequent time-gated truncation. Photothermal radiation is detected with an infrared camera while exciting a sample with a chirped set of incident optical pulses and time-dependent photothermal signal data is processed using a method that involves performing cross-correlation and subsequent time-gated truncation. The post-cross-correlation truncation method results in depth-resolved images with axial and lateral resolution beyond the well-known thermal-diffusion-length-limited, depth-integrated nature of conventional imaging modalities. An axially resolved photothermal image sequence can be obtained, capable of reconstructing three-dimensional visualizations of photothermal features in wide classes of materials.