System and Method for Automatic Detection, Localization, and Semantic Segmentation of Anatomical Objects
First Claim
1. A method for automatic detection, localization, and segmentation of at least one anatomical object in a parameter space of an image generated by an imaging system, the method comprising:
- providing the image of the anatomical object and surrounding tissue to a processor;
developing and training a parameter space deep learning network comprising one or more convolutional neural networks to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image;
automatically locating and segmenting, via an additional convolutional neural network, the anatomical object and the surrounding tissue of the parameter space of the image;
automatically labeling the anatomical object and the surrounding tissue on the image; and
displaying the labeled image to a user.
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Accused Products
Abstract
The present invention is directed to a system and method for automatic detection, localization, and semantic segmentation of at least one anatomical object in a parameter space of an image generated by an imaging system. The method includes generating the image via the imaging system and providing the image of the anatomical object and surrounding tissue to a processor. Further, the method includes developing and training a parameter space deep learning network comprising convolutional neural networks to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image. The method also includes automatically locating and segmenting, via additional convolutional neural networks, the anatomical object and surrounding tissue of the parameter space of the image. Moreover, the method includes automatically labeling the identified anatomical object and surrounding tissue on the image. Thus, the method also includes displaying the labeled image to a user in real time.
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Citations
60 Claims
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1. A method for automatic detection, localization, and segmentation of at least one anatomical object in a parameter space of an image generated by an imaging system, the method comprising:
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providing the image of the anatomical object and surrounding tissue to a processor; developing and training a parameter space deep learning network comprising one or more convolutional neural networks to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image; automatically locating and segmenting, via an additional convolutional neural network, the anatomical object and the surrounding tissue of the parameter space of the image; automatically labeling the anatomical object and the surrounding tissue on the image; and displaying the labeled image to a user. - View Dependent Claims (3, 5, 7, 9, 11, 13, 14, 15, 17, 18, 20, 21, 22, 23, 25)
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28. An imaging system, comprising:
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at least one processor configured to perform one or more operations, the one or more operations comprising; receiving an image of at least one anatomical object and surrounding tissue, developing and training a parameter space deep learning network having one or more convolutional neural networks to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image, automatically locating and segmenting, via an additional deep learning network, the anatomical object and the surrounding tissue of the parameter space of the image, and automatically labeling the anatomical object and the surrounding tissue on the image; and a user display configured to display the labeled image to a user. - View Dependent Claims (29, 32, 34, 36, 38)
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40. A method for automatic detection, localization, and semantic segmentation of at least one anatomical object in a parameter space of an image generated by an imaging system, the method comprising:
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providing the image of the anatomical object and surrounding tissue to a processor; developing and training a parameter space deep learning network to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image; automatically locating and semantically segmenting, via one or more deep learning algorithms, the anatomical object and the surrounding tissue of the parameter space of the image; automatically labeling the anatomical object and the surrounding tissue on the image; and displaying the labeled image to a user. - View Dependent Claims (43, 45, 47, 49, 51, 53, 57, 59)
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Specification