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This paper presents a weakly supervised deep convolutional neural network-based approach to perform voxel-level 3D registration between subsequent follow-up MRI scans of the same patient. To handle the large deformation in the surrounding brain tissues due to the tumor’s mass effect we proposed curriculum learning-based training for the network. Weak supervision helps the network to concentrate more focus on the tumor region and resection cavity through a saliency detection network. Qualitative and quantitative experimental results show the proposed registration network outperformed two popular state-of-the-art methods.
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Subhashis Banerjee, Dimitrios Toumpanakis, Ashis Kumar Dhara, Johan Wikström, Robin Strand, "Deep curriculum learning for follow-up MRI registration in glioblastoma," Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124643I (3 April 2023); https://doi.org/10.1117/12.2654143