Kehan Qi1, Yu Gong1,2, Haoyun Liang1, Xin Liu1, Hairong Zheng1, and Shanshan Wang1
1Paul C Lauterbur Research Center, Shenzhen Inst. of Advanced Technology, shenzhen, China, 2Northeastern University, Shenyang, China
1Paul C Lauterbur Research Center, Shenzhen Inst. of Advanced Technology, shenzhen, China, 2Northeastern University, Shenyang, China
This study investigates task-driven MR imaging, which integrates the reconstruction with
segmentation and produces both promising reconstructed images and high-quality
segmented results.
Figure 1. The overall
workflow of the proposed task-driven MR imaging method, which consists of two key components (teacher forcing and re-weighted loss training schemes) and two
modules (reconstruction and segmentation modules).
Figure 3. Visualization of the
segmentation results of the proposed method compared with existing methods.