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Abstract #4789

Investigation of DWI with Deep Learning-based Reconstruction in the Differentiation of Benign and Malignant Breast Lesions

Tiebao Meng1, Huiming Liu1, Chuanmiao Xie1, Jialu Zhang2, and Long Qian2
1Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, China, 2MR Research, GE Healthcare, Beijing, China

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Diffusion/other diffusion imaging techniquesAs the most common malignant tumor in women, the differentiation of benign lesion from malignant breast tumors is the most essential step in early diagnosis. Recent study demonstrated that DWI could offer great help in differential diagnosis of breast tumors. The novel deep learning-based reconstruction (DLR) technique is able to increase SNR of MRI images. Using DLR, DWI images can be acquired with less NEX (fast DWI) and still maintain the image quality. This study indicated the feasibility of fast DWI protocol with DLR in the differentiation of breast benign lesions and malignant tumors.

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Keywords