Neural network for neurodegenerative disease classification

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.