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Found 7 papers, 3 papers with code
Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis
Besides, we develop a new Adrenal gLand ANalysis (ALAN) dataset with the proposed NeAR, where each case consists of a 3D shape of adrenal gland and its diagnosis label (normal vs. abnormal) assigned by experts.
Deep Active Latent Surfaces for Medical Geometries
During training the latent vectors are constrained to have the same value, which avoids overfitting.
ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging
Deep implicit shape models have become popular in the computer vision community at large but less so for biomedical applications.
Weakly Supervised Volumetric Image Segmentation with Deformed Templates
There are many approaches to weakly-supervised training of networks to segment 2D images.
Deep Active Surface Models
Active Surface Models have a long history of being useful to model complex 3D surfaces but only Active Contours have been used in conjunction with deep networks, and then only to produce the data term as well as meta-parameter maps controlling them.
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data
CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation.
Probabilistic Atlases to Enforce Topological Constraints
Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs).
