Patents by Inventor Karl Spuhler

Karl Spuhler has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Dilated convolutional neural network system and method for positron emission tomography (PET) image denoising
    Patent number: 11540798
    Abstract: A method for performing positron emission tomography (PET) image denoising using a dilated convolutional neural network system includes: obtaining, as an input to the dilated convolutional neural network system, a noisy image; performing image normalization to generate normalized image data corresponding to the noisy image; encoding the normalized image data using one or more convolutions in the dilated convolutional neural network, whereby a dilation rate is increased for each encoding convolution performed to generate encoded image data; decoding the encoded image data using one or more convolutions in the dilated convolutional neural network, whereby dilation rate is decreased for each decoding convolution performed to generate decoded image data; synthesizing the decoded image data to construct a denoised output image corresponding to the noisy image; and displaying the denoised output image on an image display device, the denoised output image having enhanced image quality compared to the noisy image.
    Type: Grant
    Filed: August 28, 2020
    Date of Patent: January 3, 2023
    Assignee: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
    Inventors: Chuan Huang, Karl Spuhler, Mario Serrano Sosa
  • DILATED CONVOLUTIONAL NEURAL NETWORK SYSTEM AND METHOD FOR POSITRON EMISSION TOMOGRAPHY (PET) IMAGE DENOISING
    Publication number: 20220287671
    Abstract: A method for performing positron emission tomography (PET) image denoising using a dilated convolutional neural network system includes: obtaining, as an input to the dilated convolutional neural network system, a noisy image; performing image normalization to generate normalized image data corresponding to the noisy image; encoding the normalized image data using one or more convolutions in the dilated convolutional neural network, whereby a dilation rate is increased for each encoding convolution performed to generate encoded image data; decoding the encoded image data using one or more convolutions in the dilated convolutional neural network, whereby dilation rate is decreased for each decoding convolution performed to generate decoded image data; synthesizing the decoded image data to construct a denoised output image corresponding to the noisy image; and displaying the denoised output image on an image display device, the denoised output image having enhanced image quality compared to the noisy image.
    Type: Application
    Filed: August 28, 2020
    Publication date: September 15, 2022
    Inventors: Chuan Huang, Karl Spuhler, Mario Serrano Sosa