摘要:
A method of bounding an anatomical object of interest in a 3-dimensional volume image includes displaying an image of at least a portion of the object, selecting a plurality of points in the displayed image, at least a first and second point of the plurality of points spanning the object, forming a non-rectilinear surface bounding the plurality of points, identifying a seed point within the surface and extracting a plurality of statistical values corresponding to image voxels disposed proximate the seed point, and classifying image voxels within the surface into a first class and a second class based on the plurality of statistical values.
摘要:
A digital image editing method includes receiving a three-dimensional volume image of an anatomical object of interest, wherein the volume image is characterized by first and second mutually exclusive segmentation classes. The method also includes deriving a two-dimensional slice image from the volume image, selecting a single point on the slice image within the second segmentation class, and defining a plane in response to the selection of the single point, the plane dividing the second segmentation class into a target portion corresponding to the object and a remainder portion.
摘要:
A method of analyzing a lesion in a medical digital image using at least one point contained within a lesion to be analyzed includes propagating a wave-front surface from the point(s) for a plurality of steps; partitioning the wave-front surface into a plurality of wave-front parts wherein each wave-front part is associated with a different portion of the wave-front surface corresponding to a previous propagation step; and analyzing at least one feature associated with each wave-front part to classify anatomical structures associated with the lesion and normal anatomy within the medical digital image.
摘要:
A method of collecting information regarding an anatomical object of interest includes displaying an image characterized by a first region and a second region, wherein the first and second regions are mutually exclusive and the object is displayed within the second region, selecting first and second points spanning the object in the displayed image, at least one of the points being within the first region, and extracting a plurality of statistical values from image voxels, lying on a line segment between the first and second points, that correspond to the object.
摘要:
A method of image segmentation includes receiving a set of voxels, segmenting the set of voxels into a foreground group and a background group, and classifying voxels of the foreground group as either lesion voxels or normal anatomy voxels. The method also includes blocking the normal anatomy voxels and performing a second segmentation on voxels of the background group and the lesion voxels, the second segmentation forming a stage two foreground group comprising the lesion voxels and a portion of the voxels of the background group. The method further includes classifying voxels of the stage two foreground group as either stage two lesion voxels or stage two normal anatomy voxels.
摘要:
A method and a system are disclosed for labeling an anatomical point associated with a lesion in an organ such as a lung. The method includes: a segmentation of a vessel tree anatomical structure starting from an autonomously determined initial image point; labeling the vessel segments of the vessel tree segmentation with segment labels based on a priori anatomical knowledge, thereby creating an individualized anatomical model; receiving a user-specified image point having a location from a user and locating a nearby vessel structure; tracking along the vessel structure in a direction towards a root of a parent vessel tree until a prior labeled vessel segment is encountered in the anatomical model, and assigning the label of the encountered prior labeled vessel segment from the anatomical model as an anatomical location label of the user-specified image point.
摘要:
A method of analyzing a lesion in a medical digital image using at least one point contained within a lesion to be analyzed includes propagating a wave-front surface from the point(s) for a plurality of steps; partitioning the wave-front surface into a plurality of wave-front parts wherein each wave-front part is associated with a different portion of the wave-front surface corresponding to a previous propagation step; and analyzing at least one feature associated with each wave-front part to classify anatomical structures associated with the lesion and normal anatomy within the medical digital image.
摘要:
A method of bounding an anatomical object of interest in a 3-dimensional volume image includes displaying an image of at least a portion of the object, selecting a plurality of points in the displayed image, at least a first and second point of the plurality of points spanning the object, forming a non-rectilinear surface bounding the plurality of points, identifying a seed point within the surface and extracting a plurality of statistical values corresponding to image voxels disposed proximate the seed point, and classifying image voxels within the surface into a first class and a second class based on the plurality of statistical values.
摘要:
A method of image segmentation includes receiving a set of voxels, segmenting the set of voxels into a foreground group and a background group, and classifying voxels of the foreground group as either lesion voxels or normal anatomy voxels. The method also includes blocking the normal anatomy voxels and performing a second segmentation on voxels of the background group and the lesion voxels, the second segmentation forming a stage two foreground group comprising the lesion voxels and a portion of the voxels of the background group. The method further includes classifying voxels of the stage two foreground group as either stage two lesion voxels or stage two normal anatomy voxels.
摘要:
A method and a system are disclosed for labeling an anatomical point associated with a lesion in an organ such as a lung. The method includes: a segmentation of a vessel tree anatomical structure starting from an autonomously determined initial image point; labeling the vessel segments of the vessel tree segmentation with segment labels based on a priori anatomical knowledge, thereby creating an individualized anatomical model; receiving a user-specified image point having a location from a user and locating a nearby vessel structure; tracking along the vessel structure in a direction towards a root of a parent vessel tree until a prior labeled vessel segment is encountered in the anatomical model, and assigning the label of the encountered prior labeled vessel segment from the anatomical model as an anatomical location label of the user-specified image point.