Neural Network for Neurodegenerative Disease Classification
AssigneeSiemens Medical Solutions USA, Inc.
InventorsRachid Fahmi, Sven Zuehlsdorff, Ludovic Sibille
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Abstract
A method for configuring a neural network comprises: accessing a plurality of three-dimensional (3D) emission image data sets collected by an emission scanner from respective brains of respective subjects; transforming each of the plurality of 3D emission image data sets to a respective two-dimensional (2D) image; cropping portions of each respective 2D image to remove image data corresponding to tissue outside of a striatum of each of the respective brains, to form respective cropped 2D striatum images; and training a neural network to detect a presence of a Parkinsonian syndrome using the cropped 2D striatum images.
Claims20
A method for configuring a neural network, comprising:
- accessing a plurality of three-dimensional (3D) emission image data sets collected by an emission scanner from respective brains of respective subjects;
- transforming each of the plurality of 3D emission image data sets to a respective two-dimensional (2D) image;
- cropping portions of each respective 2D image to remove image data corresponding to tissue outside of a striatum of each of the respective brains, to form respective cropped 2D striatum images;
- and
- training a neural network to detect a presence of a Parkinsonian syndrome using the cropped 2D striatum images.
A system for configuring a neural network, comprising:
- a processor coupled to access a plurality of three-dimensional (3D) emission image data sets collected by an emission scanner from respective brains of respective subjects;
- the processor configured to transform each of the plurality of 3D emission image data sets to a respective two-dimensional (2D) image;
- the processor configured to crop portions of each respective 2D image to remove image data corresponding to tissue outside of a striatum of each of the respective brains, to form respective cropped 2D striatum images;
- and
- a neural network configured to receive the cropped 2D striatum images for training the neural network to detect a presence of a Parkinsonian syndrome using the cropped 2D striatum images.
A non-transitory, machine readable storage medium encoded with program instructions, such that when a processor executes the program instructions, the program instructions configure the processor to perform a method for configuring a neural network, comprising:
- accessing a plurality of three-dimensional (3D) emission image data sets collected by an emission scanner from respective brains of respective subjects;
- transforming each of the plurality of 3D emission image data sets to a respective two-dimensional (2D) image;
- cropping portions of each respective 2D image to remove image data corresponding to tissue outside of a striatum of each of the respective brains, to form respective cropped 2D striatum images;
- and
- training a neural network to detect a presence of a Parkinsonian syndrome using the cropped 2D striatum images.
Dependencies are inferred from the claim text.