Patents by Inventor Christine I. Podilchuk

Christine I. Podilchuk 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: 20200194108
    Abstract: A device to detect an object in a medical image is described. An image analysis application, executed by the device, receives the medical image as an input. The medical image is next partitioned to sub-regions. Parts of the object are detected in a selection of the sub-regions using a deep-learning neural network (DNN) model. Bounding boxes for the selection are also determined. The bounding boxes are evaluated based on a confidence score detected as above a threshold level. The confidence score designates the parts as contained within the selection. Next, a region of interest (ROI) is determined as a group including the selection. Similar orientations associated with the bounding boxes are comparable to similar orientations of a positive training model of the DNN model. Furthermore, the selection is designated as the ROI within the medical image. The medical image is provided with the ROI to a user.
    Type: Application
    Filed: December 13, 2018
    Publication date: June 18, 2020
    Applicant: Rutgers, The State University of New Jersey
    Inventors: Christine I. Podilchuk, Richard Mammone
  • Publication number: 20200184635
    Abstract: A system and method is disclosed to reduce variation of the clinical decision making process when an image reporting and data system (IRADS) for medical diagnosis is used. Image reporting and data systems provide guidelines for an operator to identify images as belonging to one of a number of categories and specific clinical actions are then recommended based upon such categories. Some clinical actions such as biopsies may be recommended by IRADS even when they are not necessary. The present inventive concept is configured to utilize a Computer-Assisted Diagnosis (CAD) system that is specifically programmed to minimize discrepancies between the recommended clinical actions of an individual or specific group of experts using the standard IRADS process and the optimum clinical actions based on correlation with biopsy proven data. The resulting CAD system reduces the number of unnecessary clinical actions such as biopsies based on the operator's error profile.
    Type: Application
    Filed: July 1, 2019
    Publication date: June 11, 2020
    Applicant: Koios Medical, Inc.
    Inventors: Christine I. PODILCHUK, Ajit JAIRAJ, Lev BARINOV, William HULBERT, Richard MAMMONE
  • Patent number: 10453570
    Abstract: A device to enhance and present a medical image using a corrective mechanism is described. An image analysis application executed by the device captures a digital copy of the medical image displayed on a display device. A flawed photography effect associated with the digital copy is identified by processing the digital copy. Next, the digital copy is enhanced based on the flawed photography effect. Furthermore, the enhanced digital copy can be processed with an artificial intelligence mechanism to generate an annotation. The annotation is associated with a cancer identification. In addition, the enhanced digital copy and the annotation are displayed.
    Type: Grant
    Filed: November 14, 2018
    Date of Patent: October 22, 2019
    Assignee: SONAVISTA, INC.
    Inventors: Christine I. Podilchuk, Richard Mammone
  • Publication number: 20190223845
    Abstract: A method and means to utilize machine learning to train a device to generate a confidence level indicator (CLI). The device is a CAD system that has been initially trained using initial machine learning to recommend classifications for image features presented to the device. Probabilistic classification is utilized to incorporate intermediate values given by a human operator to better indicate a level of confidence of the CAD system's recommendations as to what classes should be associated with certain image features.
    Type: Application
    Filed: August 11, 2017
    Publication date: July 25, 2019
    Applicant: Koios Medical, Inc.
    Inventors: Christine I. PODILCHUK, Ajit JAIRAJ, Lev BARINOV, William HULBERT, Richard MAMMONE
  • Patent number: 10339650
    Abstract: A system and method is disclosed to reduce variation of the clinical decision making process when an image reporting and data system (IRADS) for medical diagnosis is used. Image reporting and data systems provide guidelines for an operator to identify images as belonging to one of a number of categories and specific clinical actions are then recommended based upon such categories. Some clinical actions such as biopsies may be recommended by IRADS even when they are not necessary. The present inventive concept is configured to utilize a Computer-Assisted Diagnosis (CAD) system that is specifically programmed to minimize discrepancies between the recommended clinical actions of an individual or specific group of experts using the standard IRADS process and the optimum clinical actions based on correlation with biopsy proven data. The resulting CAD system reduces the number of unnecessary clinical actions such as biopsies based on the operator's error profile.
    Type: Grant
    Filed: July 1, 2016
    Date of Patent: July 2, 2019
    Assignee: Koios Medical, Inc.
    Inventors: Christine I. Podilchuk, Ajit Jairaj, Lev Barinov, William Hulbert, Richard Mammone
  • Patent number: 10311570
    Abstract: A mobile device to provide a medical image based distortion correction mechanism is described. An image analysis application, executed by the mobile device, captures a digital copy of the medical image with a camera component in response to a user action. Distortion(s) associated with the digital copy are identified by processing the digital copy with deep neural network (DNN) model(s). Next, a manual correction description is determined to correct the distortion(s) in relation to the camera component and the medical image. Furthermore, a notification to recapture the digital copy is provided to the user. The notification includes the manual correction description. Additionally, in response to another user action to correct the distortion(s) or a failure to detect the user execute manual correction(s) associated with the distortion(s) within a time period, the distortion(s) within the digital copy are corrected and the corrected digital copy is provided to the user.
    Type: Grant
    Filed: December 7, 2018
    Date of Patent: June 4, 2019
    Assignee: SONAVISTA, INC.
    Inventors: Christine I. Podilchuk, Richard Mammone
  • Patent number: 10290084
    Abstract: A device to correct an image blur within a medical image is described. An image analysis application executed by the device receives the medical image from a medical image provider. Next, the image blur is detected within the medical image by analyzing the medical image. The medical image is subsequently processed with a deep learning model to correct the image blur. In response to the processing, a de-blurred medical image is generated. The de-blurred medical image is provided for a presentation or a continued analysis.
    Type: Grant
    Filed: November 14, 2018
    Date of Patent: May 14, 2019
    Assignee: SONAVISTA, INC.
    Inventors: Christine I. Podilchuk, Richard Mammone
  • Patent number: 10290101
    Abstract: A device to provide a heat map based medical image diagnostic mechanism is described. An image analysis application executed by the device receives a medical image from a medical image provider. A region of interest (ROI) is determined or provided by a user. A disease state score including a malignancy score is calculated for the ROI. Next, the ROI is partitioned into sub-regions. Impact values associated with the sub-regions are also determined. The impact values indicate the influence of a sub-region on the disease state score. Furthermore, annotations are determined based on pixel values associated with the sub-region. A heat map of the sub-regions is also generated based on the impact values. The heat map is labeled with the annotations. Next, the heat map is overlaid on the ROI. The medical image is provided with the heat map to the user.
    Type: Grant
    Filed: December 7, 2018
    Date of Patent: May 14, 2019
    Assignee: SONAVISTA, INC.
    Inventors: Christine I. Podilchuk, Richard Mammone
  • Patent number: 9934567
    Abstract: A system and method is disclosed to reduce variation of the clinical decision making process when an image reporting and data system (IRADS) for medical diagnosis is used. Image reporting and data systems provide guidelines for an operator to identify images as belonging to one of a number of categories and specific clinical actions are then recommended based upon such categories. Some clinical actions such as biopsies may be recommended by IRADS even when they are not necessary. The present inventive concept is configured to utilize a Computer-Assisted Diagnosis (CAD) system that is specifically programmed to minimize discrepancies between the recommended clinical actions of an individual or specific group of experts using the standard IRADS process and the optimum clinical actions based on correlation with biopsy proven data. The resulting CAD system reduces the number of unnecessary clinical actions such as biopsies based on the operator's error profile.
    Type: Grant
    Filed: March 6, 2017
    Date of Patent: April 3, 2018
    Assignee: ClearView Diagnostics, Inc.
    Inventors: Christine I. Podilchuk, Ajit Jairaj, Lev Barinov, William Hulbert, Richard Mammone
  • Publication number: 20170200268
    Abstract: A system and method is disclosed to reduce variation of the clinical decision making process when an image reporting and data system (IRADS) for medical diagnosis is used. Image reporting and data systems provide guidelines for an operator to identify images as belonging to one of a number of categories and specific clinical actions are then recommended based upon such categories. Some clinical actions such as biopsies may be recommended by IRADS even when they are not necessary. The present inventive concept is configured to utilize a Computer-Assisted Diagnosis (CAD) system that is specifically programmed to minimize discrepancies between the recommended clinical actions of an individual or specific group of experts using the standard IRADS process and the optimum clinical actions based on correlation with biopsy proven data. The resulting CAD system reduces the number of unnecessary clinical actions such as biopsies based on the operator's error profile.
    Type: Application
    Filed: March 6, 2017
    Publication date: July 13, 2017
    Applicant: ClearView Diagnostics Inc.
    Inventors: Christine I. Podilchuk, Ajit Jairaj, Lev Barinov, William Hulbert, Richard Mammone
  • Publication number: 20170200266
    Abstract: A system and method is disclosed to reduce variation of the clinical decision making process when an image reporting and data system (IRADS) for medical diagnosis is used. Image reporting and data systems provide guidelines for an operator to identify images as belonging to one of a number of categories and specific clinical actions are then recommended based upon such categories. Some clinical actions such as biopsies may be recommended by IRADS even when they are not necessary. The present inventive concept is configured to utilize a Computer-Assisted Diagnosis (CAD) system that is specifically programmed to minimize discrepancies between the recommended clinical actions of an individual or specific group of experts using the standard IRADS process and the optimum clinical actions based on correlation with biopsy proven data. The resulting CAD system reduces the number of unnecessary clinical actions such as biopsies based on the operator's error profile.
    Type: Application
    Filed: July 1, 2016
    Publication date: July 13, 2017
    Inventors: Christine I. Podilchuk, Ajit Jairaj, Lev Barinov, William Hulbert, Richard Mammone
  • Patent number: 9536054
    Abstract: A method and means to utilize machine learning to train a device to generate a confidence level indicator (CLI). The device is a CAD system that has been initially trained using initial machine learning to recommend classifications for image features presented to the device. Probabilistic classification is utilized to incorporate intermediate values given by a human operator to better indicate a level of confidence of the CAD system's recommendations as to what classes should be associated with certain image features.
    Type: Grant
    Filed: August 11, 2016
    Date of Patent: January 3, 2017
    Assignee: ClearView Diagnostics Inc.
    Inventors: Christine I. Podilchuk, Ajit Jairaj, Lev Barinov, William Hulbert, Richard Mammone
  • Patent number: 5481308
    Abstract: A method of coding a set of multi- level signals, such as video signals comprises filtering the set of multi-level signals into one or more sets of multi-level sub-band signals; allocating a first quantity of bits for use in coding a first set of sub-band signals; coding the first set of multi-level sub-band signals using zero or more of the first quantity of allocated bits; allocating a second quantity of bits for use in coding a second set of sub-band signals, the second quantity of bits comprising zero or more of the first quantity of bits not used in coding the first set of multi-level sub-band signals; and coding the second set of multi-level sub-band signals using zero or more of the second quantity of allocated bits. Three examples of the method am provided. A hardware implementation involving the use of digital signal processors operating in parallel is also provided.
    Type: Grant
    Filed: March 15, 1995
    Date of Patent: January 2, 1996
    Assignee: AT&T Corp.
    Inventors: John Hartung, Arnaud E. Jacquin, Thomas A. Michel, Christine I. Podilchuk
  • Patent number: 5371544
    Abstract: A geometric vector quantizer coding technique is illustrated in the context of a full motion video coder based on a three-dimensional sub-band framework. The original image data is decomposed into different spatial-temporal frequency bands and based on the data in each band, different quantization strategies are applied to the bands. The lowest spatial-temporal frequency band is coded using a traditional three-dimensional switched predictor and optimum scaler quantizer. The non-dominant sub-bands are coded using the vector quantization approach to efficiently encode the images while appropriately exploiting the sparse, highly structured nature of the data to design the codebooks. Variable resolution is achieved using these techniques and no training is needed to establish or maintain the codebook. A fast codebook search technique is provided for identifying the optimal codebook vector for representing a block of input data. Examples of two and three level geometric vector quantizers are also provided.
    Type: Grant
    Filed: February 7, 1992
    Date of Patent: December 6, 1994
    Assignee: AT&T Corp.
    Inventors: Arnaud E. Jacquin, Nuggehally S. Jayant, Christine I. Podilchuk
  • Patent number: 5309232
    Abstract: The present invention provides a method of coding a set of multi-level signals, such as video signals. The method comprises filtering the set of multi-level signals into one or more sets of multi-level sub-band signals; allocating a first quantity of bits for use in coding a first set of sub-band signals; coding the first set of multi-level sub-band signals using zero or more of the first quantity of allocated bits; allocating a second quantity of bits for use in coding a second set of sub-band signals, the second quantity of bits comprising zero or more of the first quantity of bits not used in coding the first set of multi-level sub-band signals; and coding the second set of multi-level sub-band signals using zero or more of the second quantity of allocated bits. Three examples of the method are provided. A hardware implementation involving the use of digital signal processors operating in parallel is also provided.
    Type: Grant
    Filed: July 16, 1993
    Date of Patent: May 3, 1994
    Assignee: AT&T Bell Laboratories
    Inventors: John Hartung, Arnaud E. Jacquin, Thomas A. Michel, Christine I. Podilchuk
  • Patent number: 5136374
    Abstract: A geometric vector quantizer coding technique is illustrated in the context of a full motion video coder based on a three-dimensional sub-band framework. The original image data is decomposed into different spatial-temporal frequency bands and based on the data in each, different quantization strategies are applied to the bands. The lowest spatial-temporal frequency band is coded using a traditional three-dimensional switched predictor and optimum scaler quantizer. The non-dominant sub-bands are coded using the vector quantization approach to efficiently encode the images while appropriately exploiting the sparse, highly structured nature of the data to design the codebooks. Variable resolution is achieved using these techniques and no training is needed to establish or maintain the codebook.
    Type: Grant
    Filed: April 3, 1990
    Date of Patent: August 4, 1992
    Assignee: AT&T Bell Laboratories
    Inventors: Nuggehally S. Jayant, Christine I. Podilchuk