The learned shape descriptor is invariant to affine transformations, including shifts, rotations and scaling. Thanks to the adopted autoencoder framework, inter-subject differences are automatically ...

Specifically, by introducing a novel squeeze-and-excitation (SE) attention mechanism based interval type-2 generalized fuzzy hyperbolic tangent autoencoder (SE-IT2GFHTA), a multi-level convolutional ...

In recent years, semi-supervised methods have been rapidly developed for three-dimensional (3D) medical image analysis ... We improved the VNet by adding a convolutional block attention module (CBAM) ...