One example method to determine a position of a probe in a surgical site with a plurality of reference structures may include receiving a three-dimensional image of the surgical site generated before the probe enters the surgical site and receiving a first two-dimensional image generated by the probe from a position within the surgical site. The three-dimensional image is associated with a first coordinate system, and the first two-dimensional image is associated with a second coordinate system. The method also includes acquiring registration to the plurality of reference structures based on the first two-dimensional image to obtain a permissible set of probe pose parameters, extracting a second two-dimensional image based on the permissible set of probe pose parameters from the three-dimensional image, and computing a correlation between the first two-dimensional image and the extracted second two-dimensional image to map the position of the probe represented by the second coordinate system to a position represented by the first coordinate system with respect to the three-dimensional image.

A method of analyzing image data comprises: obtaining a first image of a first part of an object; obtaining a second image of a second part of the object having overlap with the first part; obtaining a mapping between the first and second images; segmenting the second image to obtain a segmentation; detecting outliers in the first image by identifying extreme intensity values of elements within one or more classes of elements on the basis of the segmentation; replacing elements of the second image that correspond to at least some outliers of the first image, with replacement values, to obtain a corrected second image; and updating the segmentation by performing the segmenting on the corrected second image. The detecting outliers, the replacing, and the updating are performed iteratively until a predetermined convergence criterion is met, which represents a point where there is no significant change in the tissue and lesion segmentations.

A surgical computing system may receive usage data associated with movement of a surgical instrument and user inputs to the surgical instrument. The surgical computing system may receive motion and/or biomarker sensor data from sensing systems applied to the operator of the surgical instrument. The surgical computing system may determine, based on at least one of the usage data and/or the sensor data, a control feature for implementation by the surgical instrument. The surgical computing system may communicate the determined control feature(s) to the surgical instrument. The surgical instrument may modify its operation based on the control features.

An information processing apparatus according to an embodiment includes a processing circuit. The processing circuit acquires a measurement field corresponding to a spatial distribution of a predetermined physical quantity in a subject of measurement. The processing circuit calculates an unknown quantity in the subject of measurement based on a first equation between the measurement field and the unknown quantity having spatial dependence, and on the acquired measurement field. The first equation is one that is acquired based on a second equation expressing a dual field divergence of which can be expressed using the measurement field, by using the measurement field and the unknown quantity, and on the Helmholtz decomposition of the dual field.

A method of transcranial brain optical imaging including obtaining a Laser Speckle (LS) image of cranial blood vessels of a subject, obtaining a Dynamic Fluorescence (DF) image of the cranial blood vessels of the subject, and combining the LS image and the DF image producing a combined color image which displays both structure of the cranial blood vessels and perfusion of blood along the cranial blood vessels. Related apparatus and methods are also described.

A harmonization system for a brain activity classifier harmonizing brain measurement data obtained at a plurality of sites to realize a discrimination process based on brain functional imaging: obtains data, for a plurality of traveling subjects as common objects of measurements at each of the plurality of measurement sites, resulting from measurements of brain activities of a predetermined plurality of brain regions of each of the traveling subjects; calculates, for each of the traveling subjects, prescribed elements of a brain functional connectivity matrix representing the temporal correlation of brain activities of a set of the plurality of brain regions; using a generalized linear mixed model, calculates measurement bias data 3108 for each element of the brain functional connectivity matrix, as a fixed effect at each measurement site with respect to an average of the corresponding element across the plurality of measurement sites and across the plurality of traveling subjects; and thereby executes a harmonizing process.

A non-invasive optical detection system and method are provided. Sample light is delivered into a target volume of interest, whereby the sample light is scattered by the target volume of interest, resulting in a sample light pattern that exits the anatomical structure. Reference light is combined with the sample light pattern to generate at least one interference light pattern, each of which may have a time varying interference component that integrates to a first value in the absence of the physiological event, and that integrates to a second greater value in the presence of the physiological event. Intensities of spatial components of each interference light pattern are detected during a measurement period. A function of the detected spatial component intensities of the interference light pattern(s) is analyzed, and a presence of the physiological event in the target volume of interest is determined based on the analysis.

The Parkinson's disease information providing apparatus using a neuromelanin image according to an aspect of the present disclosure includes an image receiving unit which acquires an MRI image obtained by capturing a brain of a patient; an image preprocessing unit which preprocesses the acquired MRI image to observe the neuromelanin region used as an image bio marker of the Parkinson's disease; an image processing unit which analyzes the preprocessed MRI image to classify a first image including the neuromelanin region and detects the neuromelanin region from the classified first image; and an image analyzing unit which diagnoses whether the patient has the Parkinson's disease by analyzing whether the detected the neuromelanin region is normal.

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.

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.