Abstract #0414
Automated Arterial Input Function Detection in Ascending Aorta for Breast DCE-MRI
Venkata Veerendranadh Chebrolu 1 , Dattesh D Shanbhag 1 , Sheshadri Thiruvenkadam 1 , Sandeep Kaushik 1 , Uday Patil 1 , Patrice Hervo 2 , Sandeep N Gupta 3 , and Rakesh Mullick 4
1
Medical Image Analysis Lab, GE Global
Research, Bangalore, Karnataka, India,
2
GE
Healthcare, Buc, France,
3
Biomedical
Image Processing Lab, GE Global Research, Niskayuna, NY,
United States,
4
Diagnostics
and Biomedical Technologies, GE Global Research,
Bangalore, Karnataka, India
DCE-MRI and pharmacokinetic (pK) model parameters
derived from the DCE data have been commonly used for
characterizing tumor vascular properties quantitatively.
The accuracy of pK parameters depends on the choice of
arterial input function (AIF). Partial volume effects
due to horizontal course of the axillary artery in the
axial plane, motion from pulsation and breathing may
reduce the accuracy of the AIF selected from the
axillary arteries. In this work we demonstrate a
completely automated method for detection of AIF in the
ascending aorta for breast DCE MRI and compare the
results with AIF manually selected by an experienced
radiologist.
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