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Abstract #1250

Stroke analysis with fully automatic multi-contrast MR image registration

Weijian Huang1, Yulon Qi2, Qiang He3, Ting Ma4, Xin Liu1, Guanxun Cheng2, Hairong Zheng1, and Shanshan Wang1
1Paul C Lauterbur Research Center, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, Shenzhen, China, 2Radiology department, Peking University Shenzhen Hospital, shenzhen, China, 3United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China, 4Pengcheng Laboratory, Shenzhen, China

Stroke is a leading cause of death and disability worldwide. However, the misalignment between multi-contrast MR images bring difficulties in identifying the lesions. We propose an automatic framework including affine and deformation transformation for multi-contrast stroke images registration. In the framework, a new inverse operation is proposed to maintain the topology of images and a background suppression loss function is designed to optimize background predictions. The method achieves the best Dice score of 0.826 compared to 5 state-of-the-art methods. Moreover, our method is about 17 times faster than the most competitive method SyN when testing on a same CPU.

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