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Abstract #3672

Isotropic 3D high-resolution T2-weighted breast MRI with a deep learning constrained Compressed SENSE reconstruction: a pilot study 

Yang Fan1, Yang Jieyin1, Sun Jiayu1, Zhang Xiaoyong2, and Ling Chuntang 3
1Department of Radiology, West China hospital of Sichuan University, Chengdu, China, 2Department of Clinical Science, Philips Healthcare, Chengdu, China, 3Department of Application, Philips Healthcare, Chongqing, China


2D T2-weighted (T2WI) breast MRI is prominently used for the identification of the colliquative necrosis and cysts, and it can also contribute to the characterization of lesions as benign or malignant. However, 2D imaging is routinely used in clinical practice, which has lower resolution, slice gaps, and may suffer distortion to delineate the breast lesions. In this study, we applied the Compressed-sensing Artificial Intelligence (CS-AI) framework to further increase the spatial resolution and reduce the scan time. The results of this study demonstrated that the high-resolution T2-weighted 3D CS-AI can provide further benefits to improve the depiction of diagnostic findings of breast lesions.

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