Computer implemented method for estimating lung perfusion from thoracic computed tomography images
The present invention relates to a computer implemented method for estimating lung perfusion from CT images, comprising the steps of: providing a CT image of at least a part of the lung, in particular a CT scan taken at inspiration, and more in particular a non-contrast CT scan taken at inspiration; providing the CT image to a trained computer implemented algorithm to estimate lung perfusion based on the CT image, wherein the trained computer implemented algorithm is trained by providing a set of CT images from at least a part of the lung, in particular a CT scan taken at inspiration, and more in particular a non-contrast CT scan taken at inspiration; providing perfusion information corresponding to the CT image; and training the computer implemented algorithm to learn to estimate perfusion in a CT image based on the reference perfusion information provided during training..
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Patent| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Europäisches Patentamt - (2023) vom: 28. Nov. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
VAN RIKXOORT EVA MARJOLEIN [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Anmerkungen: |
Source: www.epo.org (no modifications made), First posted: 2023-11-28, Last update posted on www.tib.eu: 2023-12-21, Last updated: 2023-12-29 |
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| Patentnummer: |
US11826189 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA018752527 |
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| 520 | |a The present invention relates to a computer implemented method for estimating lung perfusion from CT images, comprising the steps of: providing a CT image of at least a part of the lung, in particular a CT scan taken at inspiration, and more in particular a non-contrast CT scan taken at inspiration; providing the CT image to a trained computer implemented algorithm to estimate lung perfusion based on the CT image, wherein the trained computer implemented algorithm is trained by providing a set of CT images from at least a part of the lung, in particular a CT scan taken at inspiration, and more in particular a non-contrast CT scan taken at inspiration; providing perfusion information corresponding to the CT image; and training the computer implemented algorithm to learn to estimate perfusion in a CT image based on the reference perfusion information provided during training. | ||
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