Official Repository of STS Challenges 😎
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Updated
Sep 19, 2024 - Python
Official Repository of STS Challenges 😎
Semi-supervised Teeth Segmentation Challenge
Official Pytorch implementation of MICCAI 2024 paper (early accept, top 11%) Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
[MICCAI 2024] CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation
[MICCAI 2024] Official implementation of BrLP method from "Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge"
Carloni, G., Tsaftaris, S. A., & Colantonio, S. (2024). CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning @ MICCAI 2024 UNSURE Workshop
MARIO Challenge MICCAI 2024
Github Profile for STS Challenges 🤓
[MICCAI 2024] PEPSI: Pathology-Enhanced Pulse-Sequence-Invariant Representations for Brain MRI
Awesome Active Domain Adaptation for Medical Image Analysis
Official implementation of MICCAI 2024 paper: "Knowledge-grounded Adaptation Strategy for Vision-language Models: Building a Unique Case-set for Screening Mammograms for Residents Training".
Contribution to the SEG.A Challenge (MICCAI 2023) by Marek Wodzinski
[MICCAI 2024] TrIND: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
Holistic network for quantifying uncertainties in medical images. Work presented at the MICCAI BrainLes 2021 workshop. Published at Springer LNCS: https://link.springer.com/chapter/10.1007/978-3-031-09002-8_49
[MedIA] Accompanying paper list and source code for survey "A comprehensive survey on deep active learning in medical image analysis"
This GitHub repository hosts the notebooks and tools developed as part of this thesis to automate the extraction, processing, and analysis of data from the MICCAI 2023 conference, aiding in the systematic review and providing a structured foundation for further research in this crucial area.
Contribution to the ToothFairy Challenge (MICCAI 2023).
Code for "Pérez-García et al. 2021, Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures, MICCAI 2021".
MICCAI2023: Artifact Restoration in Histology Images with Diffusion Probabilistic Models
[MICCAI2023] Pytorch implementation for 'Regressing Simulation to Real: Unsupervised Domain Adaptation for Automated Quality Assessment in Transoesophageal Echocardiography'
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