Invention Grant
- Patent Title: Deep interactive learning for image segmentation models
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Application No.: US17201826Application Date: 2021-03-15
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Publication No.: US11176677B2Publication Date: 2021-11-16
- Inventor: Thomas Fuchs , David Joon Ho
- Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
- Applicant Address: US NY New York
- Assignee: MEMORIAL SLOAN KETTERING CANCER CENTER
- Current Assignee: MEMORIAL SLOAN KETTERING CANCER CENTER
- Current Assignee Address: US NY New York
- Agency: Foley & Lardner LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/187 ; G06T7/11 ; G06K9/62

Abstract:
Described herein are systems and methods of training models to segment images. A device may identify a training dataset. The training dataset may include images each having a region of interest. The training dataset may include first annotations. The device may train, using the training dataset, an image segmentation model having parameters to generate a corresponding first segmented images. The device may provide the first segmented images for presentation on a user interface to obtain feedback. The device may receive, via the user interface, a feedback dataset including second annotations for at least a subset of the first segmented images. Each of the second annotations may label at least a second portion of the region of interest in a corresponding image of the subset. The device may retrain, using the feedback dataset received via the user interface, the image segmentation model.
Public/Granted literature
- US20210295528A1 DEEP INTERACTIVE LEARNING FOR IMAGE SEGMENTATION MODELS Public/Granted day:2021-09-23
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