Patents by Inventor Kadri Aditya Mohan

Kadri Aditya Mohan 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).

  • Reconstruction of dynamic scenes based on differences between collected view and synthesized view
    Patent number: 11741643
    Abstract: A system for generating a 4D representation of a scene in motion given a sinogram collected from the scene while in motion. The system generates, based on scene parameters, an initial 3D representation of the scene indicating linear attenuation coefficients (LACs) of voxels of the scene. The system generates, based on motion parameters, a 4D motion field indicating motion of the scene. The system generates, based on the initial 3D representation and the 4D motion field, a 4D representation of the scene that is a sequence of 3D representations having LACs. The system generates a synthesized sinogram of the scene from the generated 4D representation. The system adjusts the scene parameters and the motion parameters based on differences between the collected sinogram and the synthesized sinogram. The processing is repeated until the differences satisfy a termination criterion.
    Type: Grant
    Filed: March 22, 2021
    Date of Patent: August 29, 2023
    Assignees: Lawrence Livermore National Security, LLC, Arizona Board of Regents on Behalf of Arizona State University
    Inventors: Hyojin Kim, Rushil Anirudh, Kyle Champley, Kadri Aditya Mohan, Albert William Reed, Suren Jayasuriya
  • 3D segmentation using space carving and 2D convolutional neural networks
    Patent number: 11568656
    Abstract: A system for generating a 3D segmentation of a target volume is provided. The system accesses views of an X-ray scan of a target volume. The system applies a 2D CNN to each view to generate a 2D multi-channel feature vector for each view. The system applies a space carver to generate a 3D channel volume for each channel based on the 2D multi-channel feature vectors. The system then applies a linear combining technique to the 3D channel volumes to generate a 3D multi-label map that represents a 3D segmentation of the target volume.
    Type: Grant
    Filed: September 25, 2020
    Date of Patent: January 31, 2023
    Assignee: Lawrence Livermore National Security, LLC
    Inventors: Kadri Aditya Mohan, Kyle Champley
  • RECONSTRUCTION OF DYNAMIC SCENES BASED ON COLLECT VIEWS
    Publication number: 20220301241
    Abstract: A system for generating a 4D representation of a scene in motion given a sinogram collected from the scene while in motion. The system generates, based on scene parameters, an initial 3D representation of the scene indicating linear attenuation coefficients (LACs) of voxels of the scene. The system generates, based on motion parameters, a 4D motion field indicating motion of the scene. The system generates, based on the initial 3D representation and the 4D motion field, a 4D representation of the scene that is a sequence of 3D representations having LACs. The system generates a synthesized sinogram of the scene from the generated 4D representation. The system adjusts the scene parameters and the motion parameters based on differences between the collected sinogram and the synthesized sinogram. The processing is repeated until the differences satisfy a termination criterion.
    Type: Application
    Filed: March 22, 2021
    Publication date: September 22, 2022
    Inventors: Hyojin Kim, Rushil Anirudh, Kyle Champley, Kadri Aditya Mohan, Albert William Reed, Suren Jayasuriya
  • 3D SEGMENTATION USING SPACE CARVING AND 2D CONVOLUTIONAL NEURAL NETWORKS
    Publication number: 20210097258
    Abstract: A system for generating a 3D segmentation of a target volume is provided. The system accesses views of an X-ray scan of a target volume. The system applies a 2D CNN to each view to generate a 2D multi-channel feature vector for each view. The system applies a space carver to generate a 3D channel volume for each channel based on the 2D multi-channel feature vectors. The system then applies a linear combining technique to the 3D channel volumes to generate a 3D multi-label map that represents a 3D segmentation of the target volume.
    Type: Application
    Filed: September 25, 2020
    Publication date: April 1, 2021
    Inventors: Kadri Aditya Mohan, Kyle Champley