Patents by Inventor Thomas A. Re

Thomas A. Re 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: 20240062523
    Abstract: Systems and methods for generating synthesized medical images of a tumor are provided. A 3D mask of an anatomical structure generated from a 3D medical image and a 3D image of a plurality of concentric spheres are received. A 3D mask of a tumor is generated based on the 3D mask of the anatomical structure and the 3D image of the plurality of concentric spheres using a first 3D generator network. A 3D intensity map of the tumor is generated based on the 3D mask of the tumor and the 3D image of the plurality of concentric spheres using a second 3D generator network. A 3D synthesized medical image of the tumor is generated based on one or more 2D slices of the 3D intensity map of the tumor and one or more 2D slices of the 3D medical image using a 2D generator network. The 3D synthesized medical image of the tumor is output.
    Type: Application
    Filed: January 30, 2023
    Publication date: February 22, 2024
    Inventors: Gengyan Zhao, Youngjin Yoo, Thomas Re, Eli Gibson, Dorin Comaniciu
  • Patent number: 11861835
    Abstract: Systems and methods for assessing expansion of an abnormality are provided. A first input medical image of a patient depicting an abnormality at a first time and a second input medical image of the patient depicting the abnormality at a second time are received. The second input medical image is registered with the first input medical image. The abnormality is segmented from 1) the first input medical image to generate a first segmentation map and 2) the registered second input medical image to generate a second segmentation map. The first segmentation map and the second segmentation map are combined to generate a combined map. Features are extracted from the first input medical image and the registered second input medical image are based on the combined map. Expansion of the abnormality is assessed based on the extracted features using a trained machine learning based network. Results of the assessment are output.
    Type: Grant
    Filed: March 25, 2021
    Date of Patent: January 2, 2024
    Assignee: Siemens Healthcare GmbH
    Inventors: Youngjin Yoo, Thomas Re, Eli Gibson, Andrei Chekkoury
  • Publication number: 20230404512
    Abstract: Systems and methods for occlusion detection in medical images are provided. An input medical image of one or more vessels in an anatomical object of a patient is received. One or more anatomical landmarks are identified in the input medical image. A first patch and one or more additional patches are extracted from the input medical image based on the identified one or more anatomical landmarks. The first patch and the one or more additional patches depict different portions of the anatomical object. Features are extracted from the first patch and the one or more additional patches using a machine learning based feature extractor network. An occlusion in the one or more vessels is detected in the first patch based on the extracted features with or without modeling features on a probability distribution function. Results of the detecting are output.
    Type: Application
    Filed: June 20, 2022
    Publication date: December 21, 2023
    Inventors: Bogdan Georgescu, Eli Gibson, Thomas Re, Dorin Comaniciu
  • Patent number: 11810291
    Abstract: Systems and methods for generating a synthesized medical image are provided. An input medical image is received. A synthesized segmentation mask is generated. The input medical image is masked based on the synthesized segmentation mask. The masked input medical image has an unmasked portion and a masked portion. An initial synthesized medical image is generated using a trained machine learning based generator network. The initial synthesized medical image includes a synthesized version of the unmasked portion of the masked input medical image and synthesized patterns in the masked portion of the masked input medical image. The synthesized patterns is fused with the input medical image to generate a final synthesized medical image.
    Type: Grant
    Filed: May 1, 2020
    Date of Patent: November 7, 2023
    Assignee: Siemens Healthcare GmbH
    Inventors: Siqi Liu, Bogdan Georgescu, Zhoubing Xu, Youngjin Yoo, Guillaume Chabin, Shikha Chaganti, Sasa Grbic, Sebastien Piat, Brian Teixeira, Thomas Re, Dorin Comaniciu
  • Publication number: 20230316532
    Abstract: Systems and methods for determining a segmentation of a hemorrhage are provided. An input medical image of a hemorrhage of a patient is received. A contour-sensitive segmentation of the hemorrhage from the input medical image is performed using a machine learning based contour-sensitive segmentation network. A detection-sensitive segmentation of the hemorrhage from the input medical image is performed using a machine learning based detection-sensitive segmentation network. A final segmentation of the hemorrhage from the input medical image is determined based on results of the contour-sensitive segmentation and results of the detection-sensitive segmentation. The final segmentation of the hemorrhage is output.
    Type: Application
    Filed: February 15, 2022
    Publication date: October 5, 2023
    Inventors: Youngjin Yoo, Eli Gibson, Bogdan Georgescu, Gengyan Zhao, Thomas Re, Jyotipriya Das, Eva Eibenberger, Andrei Chekkoury
  • Publication number: 20230102246
    Abstract: Systems and methods for generating a probabilistic tree of vessels are provided. An input medical image of vessels of a patient is received. Anatomical landmarks are identified in the input medical image. A centerline of the vessels in the input medical image is determined based on the anatomical landmarks. A probabilistic tree of the vessels is generated based on a probability of fit of the anatomical landmarks and the centerline of the vessels. The probabilistic tree of the vessels is output.
    Type: Application
    Filed: September 29, 2021
    Publication date: March 30, 2023
    Inventors: Bogdan Georgescu, Eli Gibson, Thomas Re, Dorin Comaniciu, Florin-Cristian Ghesu, Vivek Singh
  • Publication number: 20220309667
    Abstract: Systems and methods for assessing expansion of an abnormality are provided. A first input medical image of a patient depicting an abnormality at a first time and a second input medical image of the patient depicting the abnormality at a second time are received. The second input medical image is registered with the first input medical image. The abnormality is segmented from 1) the first input medical image to generate a first segmentation map and 2) the registered second input medical image to generate a second segmentation map. The first segmentation map and the second segmentation map are combined to generate a combined map. Features are extracted from the first input medical image and the registered second input medical image are based on the combined map. Expansion of the abnormality is assessed based on the extracted features using a trained machine learning based network. Results of the assessment are output.
    Type: Application
    Filed: March 25, 2021
    Publication date: September 29, 2022
    Inventors: Youngjin Yoo, Thomas Re, Eli Gibson, Andrei Chekkoury
  • Publication number: 20220293247
    Abstract: Systems and method for performing a medical imaging analysis task for making a clinical decision are provided. One or more input medical images of a patient are received. A medical imaging analysis task is performed from the one or more input medical images using a machine learning based network. The machine learning based network generates a probability score associated with the medical imaging analysis task. An uncertainty measure associated with the probability score is determined. A clinical decision is made based on the probability score and the uncertainty measure.
    Type: Application
    Filed: March 12, 2021
    Publication date: September 15, 2022
    Inventors: Eli Gibson, Bogdan Georgescu, Pascal Ceccaldi, Youngjin Yoo, Jyotipriya Das, Thomas Re, Eva Eibenberger, Andrei Chekkoury, Barbara Brehm, Thomas Flohr, Dorin Comaniciu, Pierre-Hugo Trigan
  • Patent number: 11430121
    Abstract: Systems and methods for assessing a disease are provided. Medical imaging data of lungs of a patient is received. The lungs are segmented from the medical imaging data and abnormality regions associated with a disease are segmented from the medical imaging data. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality regions. The disease may be COVID-19 (coronavirus disease 2019) or diseases, such as, e.g., SARS (severe acute respiratory syndrome), MERS (Middle East respiratory syndrome), or other types of viral and non-viral pneumonia.
    Type: Grant
    Filed: April 1, 2020
    Date of Patent: August 30, 2022
    Assignee: Siemens Healthcare GmbH
    Inventors: Shikha Chaganti, Sasa Grbic, Bogdan Georgescu, Zhoubing Xu, Siqi Liu, Youngjin Yoo, Thomas Re, Guillaume Chabin, Thomas Flohr, Valentin Ziebandt, Dorin Comaniciu, Brian Teixeira, Sebastien Piat
  • Publication number: 20220178793
    Abstract: This present invention relates to a comprehensive mold testing system capable of capturing high-resolution photographs of mold samples and wirelessly sending the digital photographs to a remote location for analysis. The mold testing system includes a vacuum-based mold capturing device and a smartphone application. The vacuum-based mold capturing device features a vacuum pump, a high-resolution/magnification camera, and a wireless communication module. The wireless communication module transmits the captured images wirelessly to the smartphone application, and the smartphone application transmits the received images to a mold specialist for testing, analysis and expert advice. The mold sample testing system eliminates the need to physically submit the mold samples to a testing laboratory, and provides a quicker turnaround time for receiving the results of the mold analysis.
    Type: Application
    Filed: December 7, 2021
    Publication date: June 9, 2022
    Inventor: Thomas Re
  • Publication number: 20210398654
    Abstract: Systems and methods for automatically detecting a disease in medical images are provided. Input medical images are received. A plurality of metrics for a disease is computed for each of the input medical images. The input medical images are clustered into a plurality of clusters based on one or more of the plurality of metrics to classify the input medical images. The plurality of clusters comprise a cluster of one or more of the input medical images associated with the disease and one or more clusters of one or more of the input medical images not associated with the disease. In one embodiment, the disease is COVID-19 (coronavirus disease 2019).
    Type: Application
    Filed: June 22, 2020
    Publication date: December 23, 2021
    Inventors: Shikha Chaganti, Sasa Grbic, Bogdan Georgescu, Guillaume Chabin, Thomas Re, Youngjin Yoo, Thomas Flohr, Valentin Ziebandt, Dorin Comaniciu
  • Publication number: 20210327054
    Abstract: Systems and methods for generating a synthesized medical image are provided. An input medical image is received. A synthesized segmentation mask is generated. The input medical image is masked based on the synthesized segmentation mask. The masked input medical image has an unmasked portion and a masked portion. An initial synthesized medical image is generated using a trained machine learning based generator network. The initial synthesized medical image includes a synthesized version of the unmasked portion of the masked input medical image and synthesized patterns in the masked portion of the masked input medical image. The synthesized patterns is fused with the input medical image to generate a final synthesized medical image.
    Type: Application
    Filed: May 1, 2020
    Publication date: October 21, 2021
    Inventors: Siqi Liu, Bogdan Georgescu, Zhoubing Xu, Youngjin Yoo, Guillaume Chabin, Shikha Chaganti, Sasa Grbic, Sebastien Piat, Brian Teixeira, Thomas Re, Dorin Comaniciu
  • Publication number: 20210304408
    Abstract: Systems and methods for assessing a disease are provided. Medical imaging data of lungs of a patient is received. The lungs are segmented from the medical imaging data and abnormality regions associated with a disease are segmented from the medical imaging data. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality regions. The disease may be COVID-19 (coronavirus disease 2019) or diseases, such as, e.g., SARS (severe acute respiratory syndrome), MERS (Middle East respiratory syndrome), or other types of viral and non-viral pneumonia.
    Type: Application
    Filed: April 1, 2020
    Publication date: September 30, 2021
    Inventors: Shikha Chaganti, Sasa Grbic, Bogdan Georgescu, Zhoubing Xu, Siqi Liu, Youngjin Yoo, Thomas Re, Guillaume Chabin, Thomas Flohr, Valentin Ziebandt, Dorin Comaniciu, Brian Teixeira, Sebastien Piat
  • Patent number: 10846875
    Abstract: System and methods are provided for localizing a target object in a medical image. The medical image is discretized into a plurality of images having different resolutions. For each respective image of the plurality of images, starting from a first image and progressing to a last image with the progression increasing in resolution, a sequence of actions is performed for modifying parameters of a target object in the respective image. The parameters of the target object comprise nonlinear parameters of the target object. The sequence of actions is determined by an artificial intelligence agent trained for a resolution of the respective image to optimize a reward function. The target object is localized in the medical image based on the modified parameters of the target object in the last image.
    Type: Grant
    Filed: February 8, 2019
    Date of Patent: November 24, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Mayalen Irene Catherine Etcheverry, Bogdan Georgescu, Sasa Grbic, Dorin Comaniciu, Benjamin L. Odry, Thomas Re, Shivam Kaushik, Bernhard Geiger, Mariappan S. Nadar
  • Publication number: 20190378291
    Abstract: System and methods are provided for localizing a target object in a medical image. The medical image is discretized into a plurality of images having different resolutions. For each respective image of the plurality of images, starting from a first image and progressing to a last image with the progression increasing in resolution, a sequence of actions is performed for modifying parameters of a target object in the respective image. The parameters of the target object comprise nonlinear parameters of the target object. The sequence of actions is determined by an artificial intelligence agent trained for a resolution of the respective image to optimize a reward function. The target object is localized in the medical image based on the modified parameters of the target object in the last image.
    Type: Application
    Filed: February 8, 2019
    Publication date: December 12, 2019
    Inventors: Mayalen Irene Catherine Etcheverry, Bogdan Georgescu, Sasa Grbic, Dorin Comaniciu, Benjamin L. Odry, Thomas Re, Shivam Kaushik, Bernhard Geiger, Mariappan S. Nadar
  • Publication number: 20190295709
    Abstract: Systems and methods are provided for determining an analytic measure of a patient population. A knowledge database comprising structured patient data for a patient population is maintained. The structured patient data is generated by processing unstructured medical imaging data for the patient population using one or more machine learning algorithms. An analytic measure of the patient population is determined based on the structured patient data of the knowledge database. The analytic measure of the patient population is output.
    Type: Application
    Filed: March 18, 2019
    Publication date: September 26, 2019
    Inventors: Guillaume Chabin, Sasa Grbic, Thomas Re, Bogdan Georgescu, Afshin Ezzi, Dorin Comaniciu, Daphne Yu
  • Publication number: 20030215413
    Abstract: The present invention provides compositions useful for skin and/or hair care that contain a retinoid in which the retinoid remains stable over a sustained period of time.
    Type: Application
    Filed: March 24, 2003
    Publication date: November 20, 2003
    Applicant: L'OREAL
    Inventors: Hani Fares, Sidney P. Foltis, Thomas Re, Alan Meyers, Mark Cornell, Isabelle Hansenne
  • Patent number: 5164406
    Abstract: The present invention provides for a composition containing a pharmacologically active agent and a selected imidazole or an imidazole derivative, such composition exhibiting enhanced penetration of the pharmacologically active agent component when a composition containing the aforementioned components is applied to skin.A method of enhancing dermal penetration of compositions containing a pharmacologically active agent is also provided.
    Type: Grant
    Filed: May 22, 1989
    Date of Patent: November 17, 1992
    Assignee: Bristol-Myers Squibb Co.
    Inventors: Michael D. Helman, Alison B. Lukacsko, Thomas A. Re, F. Christopher Zusi
  • Patent number: 5028418
    Abstract: Perspiration is decreased in an area of the skin subject to perspiration by applying to such area an antiperspirant amount of an imidazole derivative of the formula I ##STR1## wherein X is O or S and Y is Cl or H, or a dermatologically acceptable salt thereof, preferably in a dermatologically acceptable compatible vehicle.
    Type: Grant
    Filed: March 19, 1990
    Date of Patent: July 2, 1991
    Assignee: Bristol-Myers Squibb Company
    Inventors: Michael D. Helman, Thomas A. Re