Titlebook: Machine Learning in Medical Imaging; 11th International W Mingxia Liu,Pingkun Yan,Xiaohuan Cao Conference proceedings 2020 Springer Nature

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Anatomy-Aware Cardiac Motion Estimation,m cine MRI, which requires no special scanning procedure. However, current deep learning-based FT methods may result in unrealistic myocardium shapes since the learning is solely guided by image intensities without considering anatomy. On the other hand, motion estimation through learning is challen

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Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation,elationship of image features, while 3D convolution layers are hard to train from scratch due to the limited size of medical image dataset. Employing more trainable parameters and complicated connections may improve the performance of 3D CNN, however, inducing extra computational burden at the same

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tive view of their work. This book makes some new conclusions about Arendt’s theory by emphasizing how her experience of the world as displayed in her archival materials impacted her thought. Some aspects of Arendt’s life have been examined in detail before, including the fact she was stateless as w

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Pingjun Chen,Xiao Chen,Eric Z. Chen,Hanchao Yu,Terrence Chen,Shanhui Sun many technology generations of semiconductor logic and memoLife-Cycle Assessment of Semiconductors presents the first and thus far only available transparent and complete life cycle assessment of semiconductor devices. A lack of reliable semiconductor LCA data has been a major challenge to evaluati