Deterministic arterial input function selection in DCE-MRI for automation of quantitative perfusion calculation of colorectal cancer
Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion paramete...
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| Hauptverfasser: | , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2021
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| In: |
Magnetic resonance imaging
Year: 2021, Jahrgang: 75, Pages: 116-123 |
| ISSN: | 1873-5894 |
| DOI: | 10.1016/j.mri.2020.09.009 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.mri.2020.09.009 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0730725X20302423 
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| Verfasserangaben: | Christian Tönnes, Sonja Janssen, Alena-Kathrin Golla, Tanja Uhrig, Khanlian Chung, Lothar R. Schad, Frank Gerrit Zöllner |
| Zusammenfassung: | Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion parameter Ktrans. The AIF found by our algorithm has a lower mean squared error (0.0022±0.0021) in reference to the manual annotation than comparable algorithms. The error of Ktrans (21.52±17.2%) is lower than that of other algorithms. Our algorithm generates reproducible results and thus supports a robust and comparable perfusion analysis. |
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| Beschreibung: | Gesehen am 23.04.2021 |
| Beschreibung: | Online Resource |
| ISSN: | 1873-5894 |
| DOI: | 10.1016/j.mri.2020.09.009 |