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    System and methods for qualifying medical images
    2.
    发明授权
    System and methods for qualifying medical images 有权

    公开(公告)号：US12243206B2

    公开(公告)日：2025-03-04

    申请号：US17558016

    申请日：2021-12-21

    Applicant: Digital Diagnostics Inc.

    Inventor： Michael D. Abramoff ,  Ben Clark ,  Eric Talmage ,  John Casko ,  Warren Clarida ,  Meindert Niemeijer ,  Timothy Dinolfo ,  Tay Stutts

    IPC: G06T7/00 ,  G16H30/20 ,  G16H30/40

    Abstract: Disclosed is a system for qualifying medical images submitted by user for diagnostic analysis comprising: an image input module, configured to receive one or more image input by a user; an image protocol conformation module, configured to receive the one or more images from the image input module, and further configured to analyze each of the one or more images for conformity with a predefined protocol and wherein images that do not conform to the predefined protocol are flagged as non-conforming images; an image output module, configured to identify to the user each of the one or more images flagged as non-conforming and prompting the user to resubmit a new image for each of the non-conforming images; and an image resubmission module, configured to receive the user resubmitted image and provide the resubmitted image to the image protocol conformation module.

    IMAGE RETENTION AND STITCHING FOR MINIMAL-FLASH EYE DISEASE DIAGNOSIS
    4.
    发明申请
    IMAGE RETENTION AND STITCHING FOR MINIMAL-FLASH EYE DISEASE DIAGNOSIS 有权

    公开(公告)号：US20210295516A1

    公开(公告)日：2021-09-23

    申请号：US17202199

    申请日：2021-03-15

    Applicant: Digital Diagnostics Inc.

    Inventor： Warren James Clarida ,  Ryan Earl Rohret Amelon ,  Abhay Shah ,  Jacob Patrick Suther ,  Meindert Niemeijer ,  Michael David Abramoff

    IPC: G06T7/00 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30

    Abstract: Systems and methods are provided herein for minimizing retinal exposure to flash during image gathering for diagnosis. In an embodiment, a system captures a plurality of retinal images of different retinal regions. The system determines that a first portion of a first image does not meet a criterion while a second portion of the first image does meet the criterion, identifies a portion of the retina depicted in the first portion that does not meet the criterion, and determines whether the portion of the retina is depicted in a third portion of a second image and whether the third portion meets the criterion. Responsive to determining that the third portion meets the criterion, the system performs the diagnosis. Responsive to determining that the portion of the retina is not depicted in the second image, the system captures an additional image of the retinal region.

    AUTONOMOUS DIAGNOSIS OF A DISORDER IN A PATIENT FROM IMAGE ANALYSIS
    6.
    发明公开
    AUTONOMOUS DIAGNOSIS OF A DISORDER IN A PATIENT FROM IMAGE ANALYSIS 审中-公开

    公开(公告)号：US20230419485A1

    公开(公告)日：2023-12-28

    申请号：US18367384

    申请日：2023-09-12

    Applicant: Digital Diagnostics Inc.

    Inventor： Meindert Niemeijer ,  Ryan Amelon ,  Warren Clarida ,  Michael D. Abramoff

    IPC: G06T7/00 ,  G06N3/08 ,  G06V10/44 ,  G06F18/214 ,  G06N3/045 ,  G06V10/82

    CPC classification number: G06T7/0012 ,  G06N3/08 ,  G06V10/454 ,  G06F18/2148 ,  G06N3/045 ,  G06V10/82 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/30041

    Abstract: Provide are systems methods and devices for diagnosing disease in medical images. In certain aspects, disclosed is a method for training a neural network to detect features in a retinal image including the steps of: a) extracting one or more features images from a Train_0 set, a Test_0 set, a Train_1 set and a Test_1 set; b) combining and randomizing the feature images from Train_0 and Train_1 into a Training data set; c) combining and randomizing the feature images from Test_0 and Test_1 into a testing dataset; d) training a plurality of neural networks having different architectures using a subset of the training dataset while testing on a subset of the testing dataset; e) identifying the best neural network based on each of the plurality of neural networks performance on the testing data set; f) inputting images from Test_0, Train_1, Train_0 and Test_1 to the best neural network and identifying a limited number of false positives and false negative and adding the false positives and false negatives to the training dataset and testing dataset; and g) repeating steps d)-g) until an objective performance threshold is reached.

    System and Methods for Qualifying Medical Images
    7.
    发明申请
    System and Methods for Qualifying Medical Images 有权

    公开(公告)号：US20220114719A1

    公开(公告)日：2022-04-14

    申请号：US17558016

    申请日：2021-12-21

    Applicant: Digital Diagnostics Inc.

    Inventor： Michael D. Abramoff ,  Ben Clark ,  Eric Talmage ,  John Casko ,  Warren Clarida ,  Meindert Niemeijer ,  Timothy Dinolfo ,  Tay Stutts

    IPC: G06T7/00 ,  G16H30/20 ,  G16H30/40

    Abstract: Disclosed is a system for qualifying medical images submitted by user for diagnostic analysis comprising: an image input module, configured to receive one or more image input by a user; an image protocol conformation module, configured to receive the one or more images from the image input module, and further configured to analyze each of the one or more images for conformity with a predefined protocol and wherein images that do not conform to the predefined protocol are flagged as non-conforming images; an image output module, configured to identify to the user each of the one or more images flagged as non-conforming and prompting the user to resubmit a new image for each of the non-conforming images; and an image resubmission module, configured to receive the user resubmitted image and provide the resubmitted image to the image protocol conformation module.

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