Cover Image

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Tönnes, Christian (Author) , Janssen, Sonja (Author) , Golla, Alena-Kathrin (Author) , Uhrig, Tanja (Author) , Chung, Khanlian (Author) , Schad, Lothar R. (Author) , Zöllner, Frank G. (Author)
Format: Article (Journal)
Language:English
Published: 2021
In: Magnetic resonance imaging
Year: 2021, Volume: 75, Pages: 116-123
ISSN:1873-5894
DOI:10.1016/j.mri.2020.09.009
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.mri.2020.09.009
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0730725X20302423
Get full text
Author Notes:Christian Tönnes, Sonja Janssen, Alena-Kathrin Golla, Tanja Uhrig, Khanlian Chung, Lothar R. Schad, Frank Gerrit Zöllner
Description
Summary: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.
Item Description:Gesehen am 23.04.2021
Physical Description:Online Resource
ISSN:1873-5894
DOI:10.1016/j.mri.2020.09.009

Similar Items