SYSTEM AND METHOD FOR GENERATING A 3D MODEL OF ANATOMICAL STRUCTURE USING A PLURALITY OF 2D IMAGES
First Claim
1. A method for generating a three dimensional (3D) model of an internal anatomical structure of a patient using a plurality of two dimensional (2D) images acquired using a camera, comprising the steps of:
- searching the plurality of 2D images to detect correspondence points of image features across at least two images;
determining camera motion parameters using the correspondence points for a sequence of at least two 2D images taken at different locations by the camera moving within the internal anatomical structure;
computing dense stereo maps for 2D image pairs that are temporally adjacent;
forming a 3D model that is consistent by fusing together multiple 2D images which are applied to a plurality of integrated 3D model segments; and
displaying the 3D model of the patient'"'"'s anatomical structure to a user on a display device.
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Abstract
A system and method are provided for generating a three dimensional (3D) model of an anatomical structure of a patient using a plurality of two dimensional (2D) images acquired using a camera. The method includes the operation of searching the plurality of 2D images to detect correspondence points of image features across at least two images. Camera motion parameters can be determined using the correspondence points for a sequence of at least two images taken at different locations by the camera moving within the internal anatomical structure. A further operation is computing dense stereo maps for 2D image pairs that are temporally adjacent. A consistent 3D model can be formed by fusing together multiple 2D images which are applied to a plurality of integrated 3D model segments. Then the 3D model of the patient'"'"'s internal anatomical structure can be displayed to a user on a display device.
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Citations
20 Claims
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1. A method for generating a three dimensional (3D) model of an internal anatomical structure of a patient using a plurality of two dimensional (2D) images acquired using a camera, comprising the steps of:
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searching the plurality of 2D images to detect correspondence points of image features across at least two images; determining camera motion parameters using the correspondence points for a sequence of at least two 2D images taken at different locations by the camera moving within the internal anatomical structure; computing dense stereo maps for 2D image pairs that are temporally adjacent; forming a 3D model that is consistent by fusing together multiple 2D images which are applied to a plurality of integrated 3D model segments; and displaying the 3D model of the patient'"'"'s anatomical structure to a user on a display device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for generating a 3D model from a plurality of 2D images, comprising the steps of:
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initiating a 2D image salient feature search for a first image to identify correspondence points between the first image and subsequent 2D images; calculating camera motion parameters from subsequent 2D images using correspondence points between the first 2D image and subsequent 2D images; performing key frame selection procedures utilizing stochastic analysis to lower camera error parameters and enhance 3 D positions of feature points to thereby significantly increase the convergence probability of a bundle adjustment and computation of dense depth maps with increased accuracy; forming a 3D model that is consistent by fusing together multiple 2D images which are applied to a plurality of integrated 3D model segments; and generating texture fusion for textures applied to the 3D model utilizing the 2D image sequence and the computed dense depth map data in order to enhance realism of the 3D model. - View Dependent Claims (12, 13, 14)
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15. A method for generating a three dimensional (3D) model of a patient'"'"'s internal anatomical structure by analyzing a plurality of 2D images acquired using a camera, comprising the steps of:
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searching the plurality of 2D images to detect correspondence points of image features across at least two 2D images; estimating camera motion parameters using the correspondence points for a sequence of at least two images taken at different times and locations by the camera moving within the internal anatomical structure; determining 3D model points by triangulation using an average of two lines of sight from at least two 2D images; computing dense stereo maps between 2D image pairs that are temporally adjacent by fusing a matching measure from the image pair with multiple baselines from multiple 2D images into a single matching measure; applying a texture map that is fused together from a plurality of 2D images related to the 3D model point; and displaying the 3D model of the patient'"'"'s internal anatomical structure to a user on a display device. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification