Invention Grant
- Patent Title: Systems, methods, and media for automatically transforming a digital image into a simulated pathology image
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Application No.: US17310305Application Date: 2020-01-28
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Publication No.: US12131461B2Publication Date: 2024-10-29
- Inventor: Mohammadhassan Izadyyazdanabadi , Mark C. Preul , Evgenii Belykh , Yezhou Yang
- Applicant: DIGNITY HEALTH , Arizona Board of Regents on behalf of Arizona State University
- Applicant Address: US CA San Francisco
- Assignee: DIGNITY HEALTH,ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
- Current Assignee: DIGNITY HEALTH,ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
- Current Assignee Address: US CA San Francisco; US AZ Scottsdale
- Agency: QUARLES & BRADY LLP
- International Application: PCT/US2020/015332 2020.01.28
- International Announcement: WO2020/159935A 2020.08.06
- Date entered country: 2021-07-27
- Main IPC: G06T7/00
- IPC: G06T7/00 ; A61B1/00 ; A61B1/06 ; A61B1/313 ; A61B90/20 ; G06N3/045

Abstract:
In accordance with some embodiments of the disclosed subject matter, systems, methods, and media for automatically transforming a digital image into a simulated pathology image are provided. In some embodiments, the method comprises: receiving a content image from an endomicroscopy device; receiving, from a hidden layer of a convolutional neural network (CNN) trained to recognize a multitude of classes of common objects, features indicative of content of the content image; receiving, providing a style reference image to the CNN; receiving, from another hidden layer of the CNN, features indicative of a style of the style reference image; receiving, from the hidden layers of the CNN, features indicative of content and style of a target image; generating a loss value based on the features of the content image, the style reference image, and the target image; minimizing the loss value; and displaying the target image with the minimized loss.
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