abhi4ssj / few-shot-segmentationLinks
PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans
☆111Updated 5 years ago
Alternatives and similar repositories for few-shot-segmentation
Users that are interested in few-shot-segmentation are comparing it to the libraries listed below
Sorting:
- [MICCAI'20] Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains & A Well-organized Multi-site Dataset☆126Updated 4 years ago
- [NeurIPS 2020] Disentangling Human Error from the Ground Truth in Segmentation of Medical Images☆73Updated 2 years ago
- [TMI'20] Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data☆64Updated 4 years ago
- Semi-supervised few-shot learning for medical image segmentation☆26Updated 4 years ago
- [TMI'20] Unpaired Multi-modal Segmentation via Knowledge Distillation☆111Updated 2 years ago
- SDNet Keras implementation☆44Updated 5 years ago
- code for Marginal loss and exclusion loss for partially supervised multi-organ segmentation☆26Updated 3 years ago
- COVID-19 Pneumonia Lesion segmentation network☆88Updated 3 years ago
- Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"☆182Updated 3 years ago
- Code for tutorial at MICCAI 2022☆94Updated last year
- code for paper Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation☆122Updated 4 years ago
- Multi-task Attention-based Semi-supervised Learning framework for image segmentation☆42Updated 4 years ago
- Evaluation code of CHAOS challenge in MATLAB, Python and Julia languages.☆57Updated 5 years ago
- Code for the paper : "Weakly supervised segmentation with cross-modality equivariant constraints", available at https://arxiv.org/pdf/210…☆21Updated 2 years ago
- Code of our MIDL 2018 paper and MedIA extension: https://arxiv.org/abs/1805.04628☆68Updated 6 years ago
- Oral presentation at MIDL 2020 - Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision