Abstract #2380

MR Pulse Sequence Design with Artificial Neural Networks

Nahal Geshnizjani¹, Kenneth A. Loparo², Dan Ma³, Mark A. Griswold⁴,⁵

¹Dept. of Electrical Engineering and Computer Science, Case Western Reserve University , Cleveland, OH, United States; ²Dept. of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, United States; ³Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; ⁴Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; ⁵Dept. of Radiology, University Hospitals of Cleveland and Case Western Reserve University, Cleveland, OH, United States

This work presents a framework for automatic Pulse sequence design. We used Artificial Neural Networks (ANN) with a novel sequential block structure to design a system to automatically construct MR pulse sequences. We are able to predict a pure but extended T2-weighted signal from a TrueFisp sequence. This method can be utilized in MR Fingerprinting by designing non-traditional randomized pulse sequences for quantitative imaging