GENERATING SYNTHETIC MEDICAL IMAGES, FEATURE DATA FOR TRAINING IMAGE SEGMENTATION, AND INPAINTED MEDICAL IMAGES USING GENERATIVE MODELS
Generative models (e.g., a denoising diffusion probabilistic model ("DDPM") or other suitable generative model) are used to create synthetic medical images (e.g., synthetic digital radiographic images), feature data useful as a training data set for training an image segmentation model, inpainted medical images that depict a predicted postoperative outcome for a patient, and/or deidentified medical images in which radiographic markers have been removed..
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Patent| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Europäisches Patentamt - (2024) vom: 21. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
WYLES CODY C [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Sonstige Themen: |
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| Anmerkungen: |
Source: www.epo.org (no modifications made), First posted: 2024-03-21, Last update posted on www.tib.eu: 2024-04-08, Last updated: 2024-04-09 |
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| Patentnummer: |
WO2024059693 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA00316246X |
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| 245 | 1 | 0 | |a GENERATING SYNTHETIC MEDICAL IMAGES, FEATURE DATA FOR TRAINING IMAGE SEGMENTATION, AND INPAINTED MEDICAL IMAGES USING GENERATIVE MODELS |
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| 520 | |a Generative models (e.g., a denoising diffusion probabilistic model ("DDPM") or other suitable generative model) are used to create synthetic medical images (e.g., synthetic digital radiographic images), feature data useful as a training data set for training an image segmentation model, inpainted medical images that depict a predicted postoperative outcome for a patient, and/or deidentified medical images in which radiographic markers have been removed. | ||
| 650 | 4 | |a G16H: Healthcare informatics, i.e. information and communication technology [ict] specially adapted for the handling or processing of medical or healthcare data | |
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| 650 | 4 | |a G06T: Image data processing or generation, in general | |
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