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.

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.

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.

公开(公告)号：US11790523B2

公开(公告)日：2023-10-17

申请号：US16175318

申请日：2018-10-30

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 ,  G06F18/2148 ,  G06N3/045 ,  G06N3/08 ,  G06V10/454 ,  G06V10/82 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30041

Abstract: A device receives an input image of a portion of a patient's body, and applies the input image to a feature extraction model, the feature extraction model comprising a trained machine learning model that is configured to generate an output that comprises, for each respective location of a plurality of locations in the input image, an indication that the input image contains an object of interest that is indicative of a presence of a disease state at the respective location. The device applies the output of the feature extraction model to a diagnostic model, the diagnostic model comprising a trained machine learning model that is configured to output a diagnosis of a disease condition in the patient based on the output of the feature extraction model. The device outputs the determined diagnosis of a disease condition in the patient obtained from the diagnostic model.

公开(公告)号：US11232548B2

公开(公告)日：2022-01-25

申请号：US15466636

申请日：2017-03-22

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.