Patents by Inventor Satish Viswanath

Satish Viswanath 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).

  • Publication number: 20240070277
    Abstract: In various examples, systems for performing cloud-based updating of operating systems (e.g., root file systems) using system partitioning. For instance, a system(s) may initiate updates of the operating systems of machines, where the machines use system partitioning for the updating. More specifically, the system(s) may cause a machine to update the operating system using a standby system partition while the machine is currently running on another, active system partition. In some circumstances, the system(s) may perform these processes in order to update a cluster of machines, such as during a specific time period or at a certain frequency. By using such processes, the cluster of machines may still operate during the updating of the machines and/or even if the update fails on one or more of the machines.
    Type: Application
    Filed: December 12, 2022
    Publication date: February 29, 2024
    Inventors: Li Ge, Nivedita Viswanath, Philip Rogers, Rajat Chopra, Satish Salagame
  • Patent number: 11241190
    Abstract: Embodiments discussed herein facilitate predicting response to therapy in Crohn's disease. A first set of embodiments discussed herein relates to accessing a radiological image of a region of tissue demonstrating Crohn's disease associated with a patient; defining a mesenteric fat region by segmenting mesenteric fat represented in the radiological image; extracting a set of radiomic features from the mesenteric fat region; providing the set of radiomic features to a machine learning classifier configured to compute a probability of response to therapy in Crohn's disease based, at least in part, on the set of radiomic features; receiving, from the machine learning classifier, a probability that the region of tissue will respond to therapy; generating a classification of the patient as a responder or non-responder based, at least in part, on the probability; and displaying the classification.
    Type: Grant
    Filed: September 16, 2019
    Date of Patent: February 8, 2022
    Assignee: Case Western Reserve University
    Inventors: Satish Viswanath, Iulia Barbur
  • Publication number: 20210077009
    Abstract: Embodiments discussed herein facilitate predicting response to therapy in Crohn's disease. A first set of embodiments discussed herein relates to accessing a radiological image of a region of tissue demonstrating Crohn's disease associated with a patient; defining a mesenteric fat region by segmenting mesenteric fat represented in the radiological image; extracting a set of radiomic features from the mesenteric fat region; providing the set of radiomic features to a machine learning classifier configured to compute a probability of response to therapy in Crohn's disease based, at least in part, on the set of radiomic features; receiving, from the machine learning classifier, a probability that the region of tissue will respond to therapy; generating a classification of the patient as a responder or non-responder based, at least in part, on the probability; and displaying the classification.
    Type: Application
    Filed: September 16, 2019
    Publication date: March 18, 2021
    Inventors: Satish Viswanath, Iulia Barbur
  • Patent number: 10692607
    Abstract: Methods and apparatus associated with predicting colorectal cancer tumor invasiveness are described. One example apparatus includes a set of circuits, and a data store that stores radiological images of tissue demonstrating colorectal cancer. The set of circuits includes a circumferential resection margin (CRM) prediction circuit that generates a CRM probability score for a diagnostic radiological image, an image acquisition circuit that acquires a diagnostic radiological image of a region of tissue demonstrating colorectal cancer pathology and that provides the diagnostic radiological image to the CRM prediction circuit, and a training circuit that trains the CRM prediction circuit to quantify chemoradiation response in the region of tissue represented in the diagnostic radiological image. The training circuit trains the CRM prediction circuit using a set of composite images.
    Type: Grant
    Filed: March 21, 2016
    Date of Patent: June 23, 2020
    Assignee: Case Western Reserve University
    Inventors: Satish Viswanath, Anant Madabhushi, Jacob Antunes
  • Patent number: 10650515
    Abstract: Embodiments access an image of a region of interest (ROI) demonstrating cancerous pathology; extract radiomic features from the ROI; define a radiomic feature expression scene based on the ROI and radiomic features; generate a cluster map by superpixel clustering the expression scene; generate an expression map by repartitioning the cluster map into expression levels; compute a textural and spatial phenotypes for the expression map based on the expression levels; construct a radiomic spatial textural (RADISTAT) descriptor by concatenating the textural and spatial phenotypes; provide the RADISTAT descriptor to a machine learning classifier; receive, from the machine learning classifier, a first probability that the ROI is a responder or non-responder, or a second probability that the ROI will experience long-term survival or short-term survival, based, at least in part, on the RADISTAT descriptor; and generate a classification of the ROI as a responder or non-responder, or long-term survivor or short-term surv
    Type: Grant
    Filed: May 23, 2018
    Date of Patent: May 12, 2020
    Assignee: Case Western Reserve University
    Inventors: Anant Madabhushi, Satish Viswanath, Jacob Antunes, Pallavi Tiwari
  • Publication number: 20180342058
    Abstract: Embodiments access an image of a region of interest (ROI) demonstrating cancerous pathology; extract radiomic features from the ROI; define a radiomic feature expression scene based on the ROI and radiomic features; generate a cluster map by superpixel clustering the expression scene; generate an expression map by repartitioning the cluster map into expression levels; compute a textural and spatial phenotypes for the expression map based on the expression levels; construct a radiomic spatial textural (RADISTAT) descriptor by concatenating the textural and spatial phenotypes; provide the RADISTAT descriptor to a machine learning classifier; receive, from the machine learning classifier, a first probability that the ROI is a responder or non-responder, or a second probability that the ROI will experience long-term survival or short-term survival, based, at least in part, on the RADISTAT descriptor; and generate a classification of the ROI as a responder or non-responder, or long-term survivor or short-term surv
    Type: Application
    Filed: May 23, 2018
    Publication date: November 29, 2018
    Inventors: Anant Madabhushi, Satish Viswanath, Jacob Antunes, Pallavi Tiwari
  • Patent number: 10127660
    Abstract: Methods, apparatus, and other embodiments associated with predicting Crohn's Disease (CD) patient response to immunosuppressive (IS) therapy using radiomic features extracted from diagnostic magnetic resonance enterography (MRE). One example apparatus includes an image acquisition circuit that acquires an MRE image of a region of tissue demonstrating CD pathology, a segmentation circuit that segments a region of interest (ROI) from the diagnostic radiological image, a classification circuit that extracts a set of discriminative features from the ROI and that distinguishes the ROI as a responder or non-responder to IS therapy, and a CD prediction circuit that generates a radiomic enterographic (RET) score based on the diagnostic radiological image or the set of discriminative features. A prognosis or treatment plan may be provided based on the RET score.
    Type: Grant
    Filed: November 28, 2016
    Date of Patent: November 13, 2018
    Assignee: Case Western Reserve University
    Inventors: Anant Madabhushi, Cheng Lu, Satish Viswanath
  • Publication number: 20170193655
    Abstract: Methods, apparatus, and other embodiments associated with predicting Crohn's Disease (CD) patient response to immunosuppressive (IS) therapy using radiomic features extracted from diagnostic magnetic resonance enterography (MRE). One example apparatus includes an image acquisition circuit that acquires an MRE image of a region of tissue demonstrating CD pathology, a segmentation circuit that segments a region of interest (ROI) from the diagnostic radiological image, a classification circuit that extracts a set of discriminative features from the ROI and that distinguishes the ROI as a responder or non-responder to IS therapy, and a CD prediction circuit that generates a radiomic enterographic (RET) score based on the diagnostic radiological image or the set of discriminative features. A prognosis or treatment plan may be provided based on the RET score.
    Type: Application
    Filed: November 28, 2016
    Publication date: July 6, 2017
    Inventors: Anant Madabhushi, Cheng Lu, Satish Viswanath
  • Publication number: 20170053090
    Abstract: Methods and apparatus associated with predicting colorectal cancer tumor invasiveness are described. One example apparatus includes a set of circuits, and a data store that stores radiological images of tissue demonstrating colorectal cancer. The set of circuits includes a circumferential resection margin (CRM) prediction circuit that generates a CRM probability score for a diagnostic radiological image, an image acquisition circuit that acquires a diagnostic radiological image of a region of tissue demonstrating colorectal cancer pathology and that provides the diagnostic radiological image to the CRM prediction circuit, and a training circuit that trains the CRM prediction circuit to quantify chemoradiation response in the region of tissue represented in the diagnostic radiological image. The training circuit trains the CRM prediction circuit using a set of composite images.
    Type: Application
    Filed: March 21, 2016
    Publication date: February 23, 2017
    Inventors: Satish Viswanath, Anant Madabhushi, Jacob Antunes
  • Patent number: 9159128
    Abstract: The present invention provides a system and method for analysis of multimodal imaging and non-imaging biomedical data, using a multi-parametric data representation and integration framework. The present invention makes use of (1) dimensionality reduction to account for differing dimensionalities and scale in multimodal biomedical data, and (2) a supervised ensemble of embeddings to accurately capture maximum available class information from the data.
    Type: Grant
    Filed: January 13, 2012
    Date of Patent: October 13, 2015
    Assignee: RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
    Inventors: Anant Madabhushi, Satish Viswanath
  • Publication number: 20140037172
    Abstract: The present invention provides a system and method for analysis of multimodal imaging and non-imaging biomedical data, using a multi-parametric data representation and integration framework. The present invention makes use of (1) dimensionality reduction to account for differing dimensionalities and scale in multimodal biomedical data, and (2) a supervised ensemble of embeddings to accurately capture maximum available class information from the data.
    Type: Application
    Filed: January 13, 2012
    Publication date: February 6, 2014
    Applicant: RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
    Inventors: Anant Madabhushi, Satish Viswanath
  • Patent number: 8295575
    Abstract: This invention relates to computer-assisted diagnostics and classification of prostate cancer. Specifically, the invention relates to segmentation of the prostate boundary on MRI images, cancer detection using multimodal multi-protocol MR data; and their integration for a computer-aided diagnosis and classification system for prostate cancer.
    Type: Grant
    Filed: October 29, 2008
    Date of Patent: October 23, 2012
    Assignees: The Trustees of the University of PA., Rutgers, The State University of New Jersey
    Inventors: Michael D. Feldman, Satish Viswanath, Pallavi Tiwari, Robert Toth, Anant Madabhushi, John Tomaszeweski, Mark Rosen
  • Publication number: 20100329529
    Abstract: This invention relates to computer-assisted diagnostics and classification of prostate cancer. Specifically, the invention relates to segmentation of the prostate boundary on MRI images, cancer detection using multimodal multi-protocol MR data; and their integration for a computer-aided diagnosis and classification system for prostate cancer.
    Type: Application
    Filed: October 29, 2008
    Publication date: December 30, 2010
    Applicants: The Trustees of the University of Pennsylvania, Rutgers, The State University of New Jersey
    Inventors: Michael D Feldman, Satish Viswanath, Pallavi Tiwari, Robert Toth, Anant Madabhushi, John Tomaszeweski, Mark Rosen