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Found 4 papers, 2 papers with code
SpineParseNet: Spine Parsing for Volumetric MR Image by a Two-Stage Segmentation Framework with Semantic Image Representation
The SpineParseNet consists of a 3D graph convolutional segmentation network (GCSN) for 3D coarse segmentation and a 2D residual U-Net (ResUNet) for 2D segmentation refinement.
Unsupervised Deformable Medical Image Registration via Pyramidal Residual Deformation Fields Estimation
In fact, due to the limitation of the receptive field, the 3 x 3 kernel has difficulty in covering the corresponding features at high/original resolution.
Cross-lingual Data Transformation and Combination for Text Classification
In order to train a generalizable model, a large volume of text must be collected.
Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network
The CARN architecture is composed of a cascade amplifier network (CAN) for expressive feature embedding and a linear regression model for multiple indices estimation.
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