9.8k citations · 10.8k across the 28 of their papers we have counts for
6 papers · 1 filter
Patch-based Medical Image Segmentation using Matrix Product State Tensor Networks
Raghavendra Selvan, Erik B Dam, Søren Alexander Flensborg +1
Tensor networks are efficient factorisations of high-dimensional tensors into a network of lower-order tensors. They have been most commonly used to model entanglement in quantum m…
Continuous-Time Deep Glioma Growth Models
Jens Petersen, Fabian Isensee, Gregor Köhler +9
The ability to estimate how a tumor might evolve in the future could have tremendous clinical benefits, from improved treatment decisions to better dose distribution in radiation t…
RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy
Abraham George Smith, Jens Petersen, Cynthia Terrones-Campos +5
Organ-at-risk contouring is still a bottleneck in radiotherapy, with many deep learning methods falling short of promised results when evaluated on clinical data. We investigate th…
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
Jens Petersen, Gregor Köhler, David Zimmerer +3
Neural Processes (NPs) are a family of conditional generative models that are able to model a distribution over functions, in a way that allows them to perform predictions at test…
Common Limitations of Image Processing Metrics: A Picture Story
Annika Reinke, Minu D. Tizabi, Carole H. Sudre +90
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are…
Segmenting two-dimensional structures with strided tensor networks
Raghavendra Selvan, Erik B Dam, Jens Petersen
Tensor networks provide an efficient approximation of operations involving high dimensional tensors and have been extensively used in modelling quantum many-body systems. More rece…