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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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