Abstract #2034

An investigation of the performance of T2-weighted MR imaging with AI-assisted compressed sensing in routine clinical settings

Adiraju Karthik¹, Apoorwa Devappa², Aakaar Kapoor³, Dharmesh Singh⁴, and Dileep Kumar⁴

¹Department of Radiology, Sprint Diagnostics, Jubilee Hills, Hyderabad, India, ²Department of Radiology, Mahadevappa Rampure Medical College, Kalaburagi, India, ³Department of Radiology, City X-Rays Scan & Clinical Private Limited, New Delhi, India, ⁴Central Research Institute, Global Scientific Collaborations, United Imaging Healthcare, New Delhi, India

Synopsis

Keywords: Data Acquisition, Body, AI-assisted compressed sensing, T2-weighted ImagingT2-weighted imaging (T2WI) is an essential diagnostic tool for several diseases. However, one of the challenges faced by patients and radiology departments is the longer scanning time of MR examinations. Recent advancements in artificial intelligence (AI) and deep learning techniques have made it able to acquire images quickly while preserving high-quality image resolution. In this study, the efficacy of a deep learning-based reconstruction technique termed AI-Assisted Compressed Sensing (ACS) was evaluated qualitatively and quantitatively using T2WI in routine clinical settings for brain, spine, knee, kidney and liver.

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