Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, a method provides for editing of vascular paths by enabling a user to drag an erroneously segmented region of a selected vascular path into alignment with a more correctly segmented position that is depicted as a blood vessel in a vascular image. The method may use an energy function, defined as a function of position along the segmentation of the selected blood vessel, to determine how a vascular path is to be moved based on dragging motions provided by the user. In some instances, non-zero regions of the energy function are set based on the position of the selected region.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, a method provides for editing of vascular paths by enabling a user to drag an erroneously segmented region of a selected vascular path into alignment with a more correctly segmented position that is depicted as a blood vessel in a vascular image. The method may use an energy function, defined as a function of position along the segmentation of the selected blood vessel, to determine how a vascular path is to be moved based on dragging motions provided by the user. In some instances, non-zero regions of the energy function are set based on the position of the selected region.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, a method provides for editing of vascular paths by enabling a user to drag an erroneously segmented region of a selected vascular path into alignment with a more correctly segmented position that is depicted as a blood vessel in a vascular image. The method may use an energy function, defined as a function of position along the segmentation of the selected blood vessel, to determine how a vascular path is to be moved based on dragging motions provided by the user. In some instances, non-zero regions of the energy function are set based on the position of the selected region.

Abstract: Methods of and systems for reconstructing a vascular tree shape from vascular segments imaged in a single source 2-D projection image are described. A structuring shape comprising spatial positions of reference anatomical elements is defined, such as vascular segments in the definition of a 3-D surface model corresponding to a surface defined by an anatomical structure such as a body organ (e.g., heart). The 3-D surface model is used to create a 3-D model of anatomical elements (e.g., additional vascular segments of a cardiac vasculature) imaged in a source 2-D projection image, by back-projection to the 3-D surface model. The 3-D surface model is optionally aligned by first aligning the source 2-D projection image to the structuring shape. In some embodiments, the source 2-D projection image is registered to the 3-D surface model through the structuring shape by the source image's initial use in defining the structuring shape.

Abstract: A method of classifying an image is disclosed. The method comprises: applying a computer vision procedure to the image to detect therein candidate image regions suspected as being occupied by a target; presenting to an observer each candidate image region as a visual stimulus, while collecting neurophysiological signals from a brain of the observer; processing the neurophysiological signals to identify a neurophysiological event indicative of a detection of the target by the observer; and determining an existence of the target in the image is based, at least in part, on the identification of the neurophysiological event.

Abstract: Methods of and systems for reconstructing a vascular tree shape from vascular segments imaged in a single source 2-D projection image are described. A structuring shape comprising spatial positions of reference anatomical elements is defined, such as vascular segments in the definition of a 3-D surface model corresponding to a surface defined by an anatomical structure such as a body organ (e.g., heart). The 3-D surface model is used to create a 3-D model of anatomical elements (e.g., additional vascular segments of a cardiac vasculature) imaged in a source 2-D projection image, by back-projection to the 3-D surface model. The 3-D surface model is optionally aligned by first aligning the source 2-D projection image to the structuring shape. In some embodiments, the source 2-D projection image is registered to the 3-D surface model through the structuring shape by the source image's initial use in defining the structuring shape.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, a method provides for editing of vascular paths by enabling a user to drag an erroneously segmented region of a selected vascular path into alignment with a more correctly segmented position that is depicted as a blood vessel in a vascular image. The method may use an energy function, defined as a function of position along the segmentation of the selected blood vessel, to determine how a vascular path is to be moved based on dragging motions provided by the user. In some instances, non-zero regions of the energy function are set based on the position of the selected region.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, vascular centerlines identified by image analysis are divided into segments. Optionally, one or more candidate paths extending to the vascular root position along chains of segments are generated for each of a plurality of vascular endpoint. Selection of paths which correspond to anatomical paths of blood flow is optionally based on manual review. Optionally, paths are manually defined, for example, based on selection of a plurality of waypoints. Optionally, paths are edited by use of an active contour method that allows relative rough indication of corrections to be transformed into path changes that conform closely to the geometry of nearby vasculature.

Abstract: A method of classifying an image is disclosed. The method comprises: applying a computer vision procedure to the image to detect therein candidate image regions suspected as being occupied by a target; presenting to an observer each candidate image region as a visual stimulus, while collecting neurophysiological signals from a brain of the observer; processing the neurophysiological signals to identify a neurophysiological event indicative of a detection of the target by the observer; and determining an existence of the target in the image is based, at least in part, on the identification of the neurophysiological event.

Abstract: A method of classifying an image is disclosed. The method comprises: applying a computer vision procedure to the image to detect therein candidate image regions suspected as being occupied by a target; presenting to an observer each candidate image region as a visual stimulus, while collecting neurophysiological signals from a brain of the observer; processing the neurophysiological signals to identify a neurophysiological event indicative of a detection of the target by the observer; and determining an existence of the target in the image is based, at least in part, on the identification of the neurophysiological event.

Abstract: Methods and systems for manually assisted definition of vascular features are described. In some embodiments, vascular centerlines identified by image analysis are divided into segments. Optionally, one or more candidate paths extending to the vascular root position along chains of segments are generated for each of a plurality of vascular endpoint. Selection of paths which correspond to anatomical paths of blood flow is optionally based on manual review. Optionally, paths are manually defined, for example, based on selection of a plurality of waypoints. Optionally, paths are edited by use of an active contour method that allows relative rough indication of corrections to be transformed into path changes that conform closely to the geometry of nearby vasculature.

Abstract: A method of classifying an image is disclosed. The method comprises: applying a computer vision procedure to the image to detect therein candidate image regions suspected as being occupied by a target; presenting to an observer each candidate image region as a visual stimulus, while collecting neurophysiological signals from a brain of the observer; processing the neurophysiological signals to identify a neurophysiological event indicative of a detection of the target by the observer; and determining an existence of the target in the image is based, at least in part, on the identification of the neurophysiological event.