Method and apparatus for automated delineation of structure shape for image guided treatment planning
First Claim
1. An apparatus for delineating a structure of interest within image data, the image data comprising a subject image of a region of interest, the region of interest including the structure of interest, the image comprising a plurality of data points, the data points comprising a plurality of intensity values, the apparatus comprising:
- a processor configured to;
compute a plurality of features for a plurality of the data points, the features being indicative of intensity variations over a plurality of windows of the data points,detect a plurality of locations for a plurality of landmarks within the image based on an application of the computed features to a trained landmark detector,generate a shape estimate for the structure of interest based on the detected landmark locations, anditeratively refine, based on a sparse shape model from a shape dictionary, the shape estimate for the structure of interest.
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Abstract
Disclosed herein are techniques for performing automated structure delineation on image data using trained landmark detectors and a shape refinement tool. The landmark detectors can be trained to detect a landmark in the image data based on image features that are indicative of intensity variations over a plurality of windows of the image data points. A machine-learning algorithm can be used to train the landmark detectors. The landmarks in the image data that are detected by the trained landmark detects can be used to initialize an iterative shape refinement to thereby compute a refined shape estimate for a structure of interest such as a prostate.
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Citations
21 Claims
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1. An apparatus for delineating a structure of interest within image data, the image data comprising a subject image of a region of interest, the region of interest including the structure of interest, the image comprising a plurality of data points, the data points comprising a plurality of intensity values, the apparatus comprising:
a processor configured to; compute a plurality of features for a plurality of the data points, the features being indicative of intensity variations over a plurality of windows of the data points, detect a plurality of locations for a plurality of landmarks within the image based on an application of the computed features to a trained landmark detector, generate a shape estimate for the structure of interest based on the detected landmark locations, and iteratively refine, based on a sparse shape model from a shape dictionary, the shape estimate for the structure of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. An apparatus for training a landmark detector using a plurality of atlas images, the atlas images including location information for a landmark with respect to a structure of interest, the apparatus comprising:
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a processor configured to; collect a plurality of positive samples and a plurality of negative samples from the atlas images, compute a plurality of sample features for the collected positive and negative samples, wherein the sample features indicate intensity variations over a plurality of the positive and negative samples, and apply the computed sample features and location data associated with the computed sample features to a machine-learning algorithm to train a landmark detector to detect the landmark.
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14. An apparatus delineating a structure of interest within image data, the apparatus comprising:
a processor configured to; detect a plurality of landmarks with respect to a structure in an image; generate, for each detected landmark, at least one probability map mapping a location probability for each other detected landmark; determine, based on the probability maps, the location of the detected landmarks; and generate, based on the determined landmark locations, a shape estimate for the structure. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
Specification