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PrIntMesh: Precise Intersection Surfaces for 3D Organ Mesh Reconstruction
Deniz Sayin Mercadier, Hieu Le, Yihong Chen +3
Human organs are composed of interconnected substructures whose geometry and spatial relationships constrain one another. Yet, most deep-learning approaches treat these parts indep…
Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis
Jiancheng Yang, Rui Shi, Udaranga Wickramasinghe +3
The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol…
Deep Active Latent Surfaces for Medical Geometries
Patrick M. Jensen, Udaranga Wickramasinghe, Anders B. Dahl +2
Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often inv…
Weakly Supervised Volumetric Image Segmentation with Deformed Templates
Udaranga Wickramasinghe, Patrick M. Jensen, Mian Shah +2
There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision…
Deep Active Surface Models
Udaranga Wickramasinghe, Graham Knott, Pascal Fua
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 p…
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data
Udaranga Wickramasinghe, Edoardo Remelli, Graham Knott +1
CNN-based volumetric methods that label individual voxels now dominate the field of biomedical segmentation. However, 3D surface representations are often required for proper analy…
Probabilistic Atlases to Enforce Topological Constraints
Udaranga Wickramasinghe, Graham Knott, Pascal Fua
Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs). However, their use…