Abstract #1104
Adaptive spatio-temporal resolution for accelerated (ASTRA) DCEMRI driven by pharmacokinetic modelling
Rashmi Reddy 1 , Shasmshia Tabassum 1 , Shaikh Imam 1 , Nithin N Vajuvalli 1 , Sowmya Ramachandra 1 , and Sairam Geethanath 1
1
Medical Imaging Research Center, Dayananda
Sagar Institutions, Bangalore, karnataka, India
The proposed algorithm is based on an application of
compressed sensing (CS) on dynamic contrast enhancement
MRI (DCE-MRI). It involves the adaptive undersampling
technique wherein the acquisition of more number of
frames during the uptake aid to the improved Ktrans
value and the high resolution images obtained during
wash out aid in the improved Ve value. The technique is
carried out on Qiba dataset (QIBA_v7_Tofts) by using a
variable density Poisson mask for undersampling the
k-space data. The proposed algorithm reconstructs the
data by using combinations of the different acceleration
factors viz. 1X, 2X, 4X, 6X and 6X/4X, as a result of
which we are able to obtain better parametric maps with
reduction in acquisition time. The quality of the
reconstructed results is validated by calculating the
NMRSE values and parametric maps for the data with
different acceleration factors.
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