System and method for multi-label image segmentation
AssigneeSiemens Medical Solutions USA, Inc.
InventorLeo Grady
Life of this patent
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Abstract
A system and method for multi-label image segmentation is provided. The method comprises the steps of: receiving image data including a set of labeled image elements; mapping a change in intensities of the image data to edge weights; determining potentials for each image element in the image data; and assigning a label, based upon the determined potentials, to each image element in the image data.
Claims31
A method for multi-label image segmentation, comprising:
- receiving image data including a set of labeled image elements;
- mapping a change in intensities of the image data to edge weights;
- determining potentials for each image element in the image data based on the edge weights;
- and
- assigning a label from a set of labels, based upon the determined potentials, to each image element in the image data;
- wherein the label assigned to each image element corresponds to maxs(xxi)
- where maxs is to maximize over variable s which takes value from the set of labels, xxiis the potential at an image element i corresponding to a label s.
A system for multi-label image segmentation, comprising:
- a memory device for storing a program;
- a processor in communication with the memory device, the processor operative with the program to:
- receive image data including a set of labeled image elements;
- map a change in intensities of the image data to edge weights;
- determine potentials for each image element in the image data base don the edge weights;
- and
- assign a label from a set of labels, based upon the determined potentials, to each image element in the image data,
- wherein the label assigned to each image element corresponds to maxs(xis)
- where maxs is to maximize over variable s which takes value from the set of labels, xis is the potential at an image element i corresponding to a lable s.
A computer readable storage medium storing computer program code that, when executed by a computer, causes the computer to perform multi-label image segmentation, the computer program logic comprising:
- program code for receiving image data including a set of labeled image elements;
- program code for mapping a change in intensities of the image data to edge weights;
- program code for determining potentials for each image element in the image data based on the edge weights;
- and
- program code for assigning a label from a set of labels, based upon the determined potentials, to each image element in the image data,
- wherein the label assigned to each image element corresponds to maxs(xis)
- where maxs is to maximize over variable s which takes value from the set of lables, xjs is the potential at an image element i corresponding to a label s.
A system for multi-label image segmentation, comprising:
- means for receiving image data including a set of labeled image elements;
- means for mapping a change in intensities of the image data to edge weights;
- means for determining potentials for each image element in the image data based on the edge weights;
- and
- means for assigning a label form a set of labels, based upon the determined potentials, to each image element in the image data,
- wherein the label assigned to each image element corresponds to maxs(xis)
- where maxs is to maximize over variable s which takes value from the set of lables, xjs is the potential at an image element i corresponding to a label s.
A method for semi-automatic multi-label image segmentation, comprising:
- acquiring image data;
- marking the image data to include a set of labeled image elements;
- mapping a change in intensities of the image data to edge weights to represent the image data with random walker biases;
- determining potentials for each image element in the image databased on the edge weights, wherein the determined potentials represent the probability that a random walker starting at an image element in the image data first reaches a seed point in the image data set to unity;
- assigning a label from a set of labels, based upon the determined potentials, to each image element in the image data;
- and
- outputting a segmentation of the image data including the assigned label s,
- wherein the label assigned to each image element corresponds to maxs(xis)
- where maxs is to maximize over variable s which takes value from the set of lables, xjs is the potential at an image element i corresponding to a label s.
Dependencies are inferred from the claim text.