Abstract: Disclosed herein are systems and methods for interactive graphical user interfaces (GUIs) that users (e.g., medical professionals) can use to interact with modelled versions of brains and easily and intuitively analyze deep and/or lateral structures in the brain. A user can, for example, selectively view structures and their connectivity data (e.g., nodes and edges) relative to other structures and connectivity data over a representation of a particular patient's brain. Emphasis can be minimized for certain foreground nodes and edges (e.g., lateral structures) to make it easier for the user to focus on and analyze deeper structures that otherwise can be challenging to visualize and understand. A method can include overlaying deep and non-deep nodes on a representation of a brain, displaying the representation of the brain in a GUI, receiving user input indicating interest in focusing on one or more deep nodes, and taking an action based on the input.

Abstract: Methods and systems for measuring 3-dimensional distances on medical images are described. One example method includes receiving at least a first 2-dimensional image on a first plane and a second 2-dimensional image on a second plane, wherein the first plane and the second plane are different planes, selecting a first point on the first 2-dimensional image as a start point, selecting a second point on the second 2-dimensional image as an end point, determining a shortest path between the start point and the end point, performing a measurement of the shortest path between the start point and the end point, and, taking an action based on the measurement.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating visualization data for a selected neuro-network. In one aspect, a method comprises: receiving selection data selecting a network in a brain of a subject; processing magnetic resonance image data of the brain to identify a set of tracts that are predicted to be included in the selected network; processing the set of tracts to identify a proper subset of the set of tracts as being spurious tracts; generating a set of valid tracts by filtering the spurious tracts from the set of tracts that are predicted to be included in the selected network; providing visualization data for the selected network showing a three-dimensional spatial representation of both: (i) the valid tracts, and (ii) the spurious tracts, wherein the spurious tracts are visually distinguished from the valid tracts.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for filtering a set of tracts that are predicted to be included in a selected neuro-network. In one aspect, a method comprises: receiving selection data selecting a network of a brain, processing magnetic resonance image data of the brain to identify a set of tracts that are predicted to be included in the selected network, determining a blocking surface for the selected network, comprising: obtaining a set of parcellations for the selected network and determining, based on a respective position in the brain of each parcellation in the set of parcellations, a set of parameters defining the blocking surface, and generating filtered tract data by filtering the set of tracts that are predicted to be included in the selected network to remove tracts that intersect the blocking surface.