AneurysmNet
importedsoftware/aneurysmnet
ADAM challenge submission in MICCAI 2020, from the Kubiac team
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/Hierakonpolis/AneurysmNet
- Documentation
- unknown
- Tags
- aneurysm · convolutional-neural-networks · deep-learning · mri · segmentation
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- Paint4Brainsconvolutional-neural-networks · mri · segmentation
A brain MRI segmentation tool that provides accurate robust segmentation of problematic brain regions across the neurodegenerative spectrum. The methodology is generalisable to perform well with the…
- CapsNetsLASegconvolutional-neural-networks · segmentation
Capsule Networks and Convolutional Neural Networks for the Automated Segmentation of Left Atrium in Cardiac MRI
- kits19.MIScnnconvolutional-neural-networks · segmentation
Kidney Tumor Segmentation Challenge 2019: MIScnn - 3D Residual U-Net
- medical_image_segmentationconvolutional-neural-networks · segmentation
Medical image segmentation ( Eye vessel segmentation)
- nn-common-modulesconvolutional-neural-networks · segmentation
Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
- quickNAT_pytorchconvolutional-neural-networks · segmentation
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
- api.github.com/repos/Hierakonpolis/AneurysmNetretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2020-12-04, 7 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/52.json→ .entries["aneurysmnet"]
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