Image registration for image-guided surgery
First Claim
Patent Images
1. A method for identifying a structure within a patient image, comprising:
- generating a reference image from an image of the patient;
generating a template from at least a portion of the reference image, the template comprising a set of patches;
for each patch, generating a patch similarity map by computing a local similarity measure between the patient image and the patch for the template located at each of several candidate locations for the structure in the patient image;
combining the patch similarity maps according to spatial relationships among the set of patches in the template to obtain a global similarity map; and
identifying the structure from a template location in the patient image that corresponds to a maximum value for the global similarity map.
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Abstract
An image registration process for detecting a change in position of a surgical target, such as a tumor, within a patient is disclosed. A pre-operative model of the target and surrounding area is generated, then registered to live patient images to determine or confirm a location of the target during the course of surgery. Image registration is based on a non-iterative image processing logic that compares a similarity measure for a template of the target (generated from the pre-operative model) at one location within the live image to other locations within the live image.
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Citations
26 Claims
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1. A method for identifying a structure within a patient image, comprising:
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generating a reference image from an image of the patient; generating a template from at least a portion of the reference image, the template comprising a set of patches; for each patch, generating a patch similarity map by computing a local similarity measure between the patient image and the patch for the template located at each of several candidate locations for the structure in the patient image; combining the patch similarity maps according to spatial relationships among the set of patches in the template to obtain a global similarity map; and identifying the structure from a template location in the patient image that corresponds to a maximum value for the global similarity map. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A method for identifying a structure within a patient image, comprising:
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generating a reference image from an image of the patient; generating a template from all or part of the reference image, the template comprising a set of patches; computing similarity values between the patient image and the template for the template located at each of several candidate locations for the structure in the patient image, wherein at each template location the similarity value is computed according to steps (a) and (b), as follows; (a) for each patch, computing a local similarity value for a neighborhood of the patch'"'"'s location in the patient image, and (b) combining the local similarity values to obtain the similarity value at the template location; and identifying the structure in the patient image from a template location corresponding to a maximum of the similarity values. - View Dependent Claims (18, 19, 20)
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21. A non-transitory computer-readable medium having stored therein computer-readable instructions for a processor, wherein the instructions, when read and implemented by the processor, cause the processor to:
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generate a patch similarity map for each of a set of patches that form a template for a structure within a patient, wherein the template was generated from a reference image of the patient, and wherein the patch similarity map is generated by computing a local similarity measure between a patient image and the patch for the template located at each of several candidate locations for the structure in the patient image; combine the patch similarity maps according to spatial relationships among the set of patches in the template to obtain a global similarity map; and identify the structure from a template location in the patient image that corresponds to a maximum value for the global similarity map. - View Dependent Claims (22, 23)
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24. A method for verifying an expected location for a target structure in a patient image, comprising:
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computing similarity measures between the patient image and patches for the structure for each of a plurality of candidate locations for the structure in the patient image; generating a global similarity map from the computed similarity measures, wherein a maximum of the computed similarity measures is an expected location for the structure in the patient image; displaying the global similarity map with the patient image such that a similarity measure for each of the candidate locations is displayed with the corresponding location in the patient image; and visually comparing structure in the patient image against the similarity measures to verify that the expected location is the actual location of the target structure in the patient image. - View Dependent Claims (25, 26)
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Specification