Q3304225 (Q3304225): Difference between revisions
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(Changed label, description and/or aliases in en: Setting new description) |
(Created claim: summary (P836): With the help of a systematic analysis of self-similarity, it is planned to carry out a simulation of a complete human lung model in all characteristic functional phases based on physical, fluid and structural dynamic modulation. Building on these computation-intensive approaches, the project aims for the first time to develop a new, innovative, deep learning algorithm-based simulation approach (DLS-L) for individualised, digital lung function a...) |
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With the help of a systematic analysis of self-similarity, it is planned to carry out a simulation of a complete human lung model in all characteristic functional phases based on physical, fluid and structural dynamic modulation. Building on these computation-intensive approaches, the project aims for the first time to develop a new, innovative, deep learning algorithm-based simulation approach (DLS-L) for individualised, digital lung function analyses, which is to be used in the course of the progressive development of modern diagnostic methods and individualised therapy applications in clinical everyday life. (English) | |||||||||||||||
| Property / summary: With the help of a systematic analysis of self-similarity, it is planned to carry out a simulation of a complete human lung model in all characteristic functional phases based on physical, fluid and structural dynamic modulation. Building on these computation-intensive approaches, the project aims for the first time to develop a new, innovative, deep learning algorithm-based simulation approach (DLS-L) for individualised, digital lung function analyses, which is to be used in the course of the progressive development of modern diagnostic methods and individualised therapy applications in clinical everyday life. (English) / rank | |||||||||||||||
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| Property / summary: With the help of a systematic analysis of self-similarity, it is planned to carry out a simulation of a complete human lung model in all characteristic functional phases based on physical, fluid and structural dynamic modulation. Building on these computation-intensive approaches, the project aims for the first time to develop a new, innovative, deep learning algorithm-based simulation approach (DLS-L) for individualised, digital lung function analyses, which is to be used in the course of the progressive development of modern diagnostic methods and individualised therapy applications in clinical everyday life. (English) / qualifier | |||||||||||||||
point in time: 24 October 2021
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Revision as of 17:44, 24 October 2021
Project Q3304225 in Germany
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | No label defined |
Project Q3304225 in Germany |
Statements
325,400.0 Euro
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1 May 2021
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31 December 2023
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Treaves Research & Consult GmbH Rudek Dr.Arthur Alexander
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65835
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Mit Hilfe einer systematischen Selbstähnlichkeitsanalyse ist es geplant, eine auf physikalischen, fluid- und strukturdynamischen Mod ellierungsgrundlagen basierende Simulation eines vollständigen humanen Lungenmodells in allen charakteristischen Funktionsabschnitte n durchzuführen. Aufbauend auf diesen rechenintensiven Ansätzen soll im Rahmen des Vorhabens erstmals ein auf DeepLearning-Algorith mik basierender, neuartiger und durch seine hohe Effizienz im Vergleich zu etablierten Methoden echtzeitfähiger Simulationsansatz (m DLS-L Verfahren) für individualisierte, digitale Lungenfunktionsanalysen entwickelt werden, welcher im Zuge der fortschreitenden Ent wicklung moderner Diagnoseverfahren und individualisierter Therapieeinsätze im klinischen Alltag zum Einsatz kommen soll. (German)
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With the help of a systematic analysis of self-similarity, it is planned to carry out a simulation of a complete human lung model in all characteristic functional phases based on physical, fluid and structural dynamic modulation. Building on these computation-intensive approaches, the project aims for the first time to develop a new, innovative, deep learning algorithm-based simulation approach (DLS-L) for individualised, digital lung function analyses, which is to be used in the course of the progressive development of modern diagnostic methods and individualised therapy applications in clinical everyday life. (English)
24 October 2021
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Identifiers
DE_TEMPORARY_7007
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