Search Results for author:
Found 5 papers, 4 papers with code
Self-Supervised Nuclei Segmentation in Histopathological Images Using Attention
We show that the identification of the magnification level for tiles can generate a preliminary self-supervision signal to locate nuclei.
Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation
Image registration and segmentation are the two most studied problems in medical image analysis.
Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion
In this work we introduce Lifting Autoencoders, a generative 3D surface-based model of object categories.
Linear and Deformable Image Registration with 3D Convolutional Neural Networks
Image registration and in particular deformable registration methods are pillars of medical imaging.
Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
In this work we introduce Deforming Autoencoders, a generative model for images that disentangles shape from appearance in an unsupervised manner.
Ranked #9 on
Unsupervised Facial Landmark Detection
on MAFL
