System and method for detecting and matching anatomical stuctures using appearance and shape
First Claim
1. A method for detecting an object in an image that contains invalid data regions, the method comprising the steps of:
- determining a data mask for the image to indicate which pixels in the image are valid;
representing the data mask as an integral mask in which each pixel has a value corresponding to a total number of valid pixels in the image above and to left of the pixel;
applying a rectangular feature to the image, the rectangular feature having at least one positive region and one negative region;
determining the number of pixels in the rectangular feature that are valid using the integral mask;
approximating a mean intensity value for a region that contains invalid pixels;
determining a feature value for the rectangular feature by computing a weighted difference between a sum of intensity values in the positive and negative regions of the rectangular feature; and
using the feature value to determine if an object has been detected.
5 Assignments
0 Petitions
Accused Products
Abstract
A detection framework that matches anatomical structures using appearance and shape is disclosed. A training set of images are used in which object shapes or structures are annotated in the images. A second training set of images represents negative examples for such shapes and structures, i.e., images containing no such objects or structures. A classification algorithm trained on the training sets is used to detect a structure at its location. The structure is matched to a counterpart in the training set that can provide details about the structure'"'"'s shape and appearance.
113 Citations
71 Claims
-
1. A method for detecting an object in an image that contains invalid data regions, the method comprising the steps of:
-
determining a data mask for the image to indicate which pixels in the image are valid;
representing the data mask as an integral mask in which each pixel has a value corresponding to a total number of valid pixels in the image above and to left of the pixel;
applying a rectangular feature to the image, the rectangular feature having at least one positive region and one negative region;
determining the number of pixels in the rectangular feature that are valid using the integral mask;
approximating a mean intensity value for a region that contains invalid pixels;
determining a feature value for the rectangular feature by computing a weighted difference between a sum of intensity values in the positive and negative regions of the rectangular feature; and
using the feature value to determine if an object has been detected. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A method for detecting an object in an image comprising the steps of:
-
a). computing a feature value for a classifier in a window of the image;
b). determining if the feature value is above a predetermined threshold value;
c). if the feature value is above the threshold value, computing a subsequent feature value for a subsequent classifier in the window of the image;
d). combining the value of the feature value and the subsequent feature value;
e). determining if the combined feature value is above a combination threshold value for a current combination;
f). if the combined feature value is above the combination threshold value, repeating steps c)-e) until there are no subsequent classifiers or the combined feature value is not above the combination threshold value; and
g). using a final combined feature value to determine if an object has been detected. - View Dependent Claims (10, 11, 12)
-
-
13. A method for detecting and matching anatomical structures in an image to one or more anatomical structures in a training set of images comprising the steps of:
-
receiving a candidate image;
extracting feature values from the candidate image;
applying a classification function to detect an anatomical structure;
if an anatomical structure is detected, identifying one or more counterpart images in the training set of images by matching the extracted feature values for the candidate image to feature values of the counterpart images in the training set; and
using one or more shapes of anatomical structures in the matching counterpart images from the training set to determine a shape of the anatomical structure in the candidate image. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
-
-
26. A method for matching an anatomical structure in an image to one or more similarly shaped anatomical structures in a training set of images comprising the steps of:
-
receiving an image of a candidate anatomical structure;
extracting features from the image;
comparing features associated with similarly shaped anatomical structures to the candidate anatomical structure; and
determining the shape of the candidate anatomical structure by using the shape of at least one nearest neighbor from the training set. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34)
-
-
35. A method for detecting and tracking a deformable shape of a candidate object in an image, the shape being representing by a plurality of labeled control points, the method comprising the steps of:
-
detecting at least one control point of the deformable shape in an image frame;
for each control point associated with the candidate object, computing a location uncertainty matrix;
generating a shape model to represent dynamics of the deformable shape in subsequent image frames, the shape model comprising statistical information from a training data set of images of representative objects;
aligning the shape model to the deformable shape of the candidate object;
fusing the shape model with the deformable shape; and
estimating a current shape of the candidate object. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47)
-
-
48. A system for detecting and matching anatomical structures in an image to one or more anatomical structures in a training set of images comprising the steps of:
-
means for receiving a candidate image;
means for extracting feature values from the candidate image;
means for applying a classification function to detect an anatomical structure;
means for identifying one or more counterpart images in the training set of images by matching the extracted feature values for the candidate image to feature values of the counterpart images in the training set; and
means for using a shape of an anatomical structure in a matching counterpart image from the training set to determine a shape of the anatomical structure in the candidate image. - View Dependent Claims (49, 50, 51, 52, 53, 54, 55, 56, 57, 58)
-
-
59. A system for detecting and tracking a deformable shape of a candidate object in an image, the shape being representing by a plurality of labeled control points, the method comprising the steps of:
-
means for detecting at least one control point of the deformable shape in an image frame;
means for computing a location uncertainty matrix for each control point associated with the candidate object;
means for generating a shape model to represent dynamics of the deformable shape in subsequent image frames, the shape model comprising statistical information from a training data set of images of representative objects;
means for aligning the shape model to the deformable shape of the candidate object;
means for fusing the shape model with the deformable shape; and
means for estimating a current shape of the candidate object. - View Dependent Claims (60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71)
-
Specification