259 citations · 771 across the 27 of their papers we have counts for
6 papers · 1 filter
'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient
Christian Strack, Kelsey L. Pomykala, Heinz-Peter Schlemmer +2
With the rise in importance of personalized medicine, we trained personalized neural networks to detect tumor progression in longitudinal datasets. The model was evaluated on two d…
Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathology
Oliver Ester, Fabian Hörst, Constantin Seibold +9
The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and gl…
Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder
Jianning Li, Jana Fragemann, Seyed-Ahmad Ahmadi +2
The reconstruction loss and the Kullback-Leibler divergence (KLD) loss in a variational autoencoder (VAE) often play antagonistic roles, and tuning the weight of the KLD loss in $β…
The HoloLens in Medicine: A systematic Review and Taxonomy
Christina Gsaxner, Jianning Li, Antonio Pepe +4
The HoloLens (Microsoft Corp., Redmond, WA), a head-worn, optically see-through augmented reality display, is the main player in the recent boost in medical augmented reality resea…
Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model
Jianning Li, David G. Ellis, Antonio Pepe +4
Designing implants for large and complex cranial defects is a challenging task, even for professional designers. Current efforts on automating the design process focused mainly on…
Review of Disentanglement Approaches for Medical Applications -- Towards Solving the Gordian Knot of Generative Models in Healthcare
Jana Fragemann, Lynton Ardizzone, Jan Egger +1
Deep neural networks are commonly used for medical purposes such as image generation, segmentation, or classification. Besides this, they are often criticized as black boxes as the…