A cognitive optical system for dynamically refining imaging during a medical procedure, involving a processor operable by a set of executable instructions storable in relation to a non-transitory memory device. The processor is configured to automatically adjust an image by automatically compensating for at least one external factor affecting an anatomical area being viewed, automatically adjusting at least one imaging parameter, and automatically adjusting at least one internal control of an optical chain, whereby a quality of the image is improvable in real time.

The present disclosure relates to a novel pupilometer and method of using the pupilometer to record and analyze direct and consensual reflex of pupils to identify brain lesion locations of a patient with brain injuries.

Certain aspects of the invention provide a system and a method for treating an epileptic condition or a tumor of the brain. In one embodiment, the method of treating the epileptic condition includes acquiring inter- and post-ictal imaging profiles and from the brain of the patient and determining an ictal propagation pathway based on the profiles. A volume of cortical activation is determined for each of a plurality of virtual electrode placement positions based on the ictal propagation pathway and the virtual electrode placement position. An electrode is implanted at a position selected from the plurality of virtual electrode placement positions, based on the volume of cortical activation at the implantation position. An electrical pulse is delivered from the electrode, where the electrical pulse is of a magnitude and duration effective to at least reduce the epileptic seizure.

This disclosure describes systems, devices, and techniques for adjusting an anatomical atlas to patient anatomy. In one example, a system may include processing circuitry configured to generate, for display at a user interface, a representation of an anatomical region of a patient, generate, for display at the user interface, a representation of one or more atlas-defined anatomical structures at a first position over the representation of the anatomical region of the patient, receive a user annotation that defines an adjustment to at least one atlas-defined anatomical structure relative to the representation of the anatomical region of the patient, and adjust, based on the adjustment, the first position of the representation of the one or more atlas-defined anatomical structures to a second position of the representation of the one or more atlas-defined anatomical structures over the representation of the anatomical region of the patient.

A method of automatically evaluating resection accuracy, is provided. The method includes preoperatively obtaining a first image of a volume of patient tissue using an imaging modality configured according to a scanning parameter, and storing the scanning parameter. An identifier of a target region corresponding to a target portion of the volume is received and stored in association with the first image. A second image is obtained of a resected tissue sample from the volume, using the imaging modality configured according to the scanning parameter. Based on a comparison of the first image and the second image, a determination is made whether the entire target region is represented in the second image. The method includes controlling an output device to present an indication, based on the determination, of whether the tissue sample contains the entire target portion.

The present invention is directed to a context-based image retrieval (CBIR) system for disease estimation based on the multi-atlas framework, in which the demographic and diagnostic information of multiple atlases are weighted and fused to generate an estimated diagnosis, on a structure-by-structure basis. The present invention demonstrates high accuracy in age estimation, as well as diagnostic estimation in Alzheimer's disease. The system and the pathology-based multi atlases can be used to estimate various types of disease and pathology with the choice of patient attributes. The present invention is also directed to a method of context-based image retrieval.

A system, method, and apparatus for displaying a fused reconstructed image with a multidimensional image are disclosed. An example imaging system receives a selection corresponding to a portion of a displayed multidimensional visualization of a surgical site. At the selected portion of the multidimensional visualization, the imaging system displays a portion of a three-dimensional image which corresponds to the selected multidimensional visualization such that the displayed portion of the at least one of the three-dimensional image or model is fused with the displayed multidimensional visualization.

A computing device for use in a system for mapping brain activity of a subject includes a processor. The processor is programmed to select a plurality of measurements of brain activity that is representative of at least one parameter of a brain of the subject during a resting state. Moreover, the processor is programmed to compare at least one data point from each of the measurements with a corresponding data point from a previously acquired data set from at least one other subject. The processor is also programmed to produce at least one map for each of the measurements based on the comparison of the resting state data point and the corresponding previously acquired data point. The processor may also be programmed to categorize the brain activity in a plurality of networks in the brain based on the map.

A method of predicting the response of a subject to an antipsychotic agent is described. The method includes obtaining functional MRI (fMRI) scan data of the brain of the subject, modifying the scan data using a standardizing algorithm to provide modified scan data, calculating the value of a plurality of striatal connectivity dyads from the modified scan data using an extraction algorithm, calculating a combined score from the values of the striatal connectivity dyads using a combining algorithm; and comparing the combined score to a classifier value to determine if the subject is a responder or a non-responder. Systems for carrying out the method of predicting the response of a subject to an antipsychotic agent are also described.

A method improves a detection of a brain tissue pathology in magnetic resonance (MR) images of a patient. The method includes acquiring multiple MR imaging data for creating four different contrast maps of a patient brain. From the multiple MR imaging data, performing an estimation of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) concentration for each voxel of a part of the patient brain. From the multiple MR imaging data, segmenting the part of the patient brain in different regions-of-interest (ROIs) according to a chosen atlas. For each voxel of each of the contrast maps of the patient brain, computing, for the part of the patient brain, a deviation score. The method further includes creating from the deviation score and for each of the quantitative contrast maps, a deviation map representing the part of the brain in dependence on the deviation score calculated for each voxel.