Peripheral nerve injuries are common and lead to life-long disability for affected individuals in spite of surgical treatments. Yet an unsolved clinical problem is misdirected axonal outgrowth with lack of sufficient functional reconnections. New insights in cellular structure and mechanisms of nerve regeneration are needed, which leads to new prospects for intervention. We focus on repair and reconstruction of injured nerves to investigate interaction between spatial outgrowth of axons and its environment, particularly presence and formation of blood vessels. We assemble experimental rat models, including a diabetic rat model, in which nerves are repaired and reconstructed using novel strategies, such as application of silk threads between severed nerve ends. The peripheral nerves will be investigated using applied synchrotron imaging and quantitative image analysis. The gained insights will eventually lead to improved treatment strategies and quality of life for patients.

Data for CVPR 2020 paper Sparse Layered Graphs for Multi-Object Segmentation.

Related notebooks can be found here:
http://doi.org/10.11583/DTU.12016941
data.zipContains images used in the notebooks and paper experiments.
NT32_tomo3_.raw
This is a micro-CT scan of hand nerves used in the paper. The volume is 2048x2048x2048 uint16.
NT32_cLineLabel_scale4_preSegm_v3.nii.gz
This is a segmentation of the center lines of 216 nerves in the NT32 scan. The segmentation is made at four times lower resolution than NT32_tomo3_.raw and has a size of 512x512x512.
The NT32 dataset was previously used in the paper Three-dimensional architecture of human diabetic peripheral nerves revealed by X-ray phase contrast holographic nanotomography.

Data for CVPR 2020 paper Sparse Layered Graphs for Multi-Object Segmentation.

Related notebooks can be found here:
http://doi.org/10.11583/DTU.12016941
data.zipContains images used in the notebooks and paper experiments.
NT32_tomo3_.raw
This is a micro-CT scan of hand nerves used in the paper. The volume is 2048x2048x2048 uint16.
NT32_cLineLabel_scale4_preSegm_v3.nii.gz
This is a segmentation of the center lines of 216 nerves in the NT32 scan. The segmentation is made at four times lower resolution than NT32_tomo3_.raw and has a size of 512x512x512.
The NT32 dataset was previously used in the paper Three-dimensional architecture of human diabetic peripheral nerves revealed by X-ray phase contrast holographic nanotomography.