@stefanocerri.bsky.social @asbjornmunk.bsky.social @peirong26.bsky.social
Read more about the challenge and signup on:
➡️ fomo25.github.io
🤗: huggingface.co/datasets/FOMO25/FOMO-MRI
💻: github.com/fomo25/baseline-codebase
Read more about the challenge and signup on:
➡️ fomo25.github.io
🤗: huggingface.co/datasets/FOMO25/FOMO-MRI
💻: github.com/fomo25/baseline-codebase
Participants are provided with a baseline framework to carry out both pretraining and finetuning, enabling them to concentrate on specific components of the workflow.
Participants are provided with a baseline framework to carry out both pretraining and finetuning, enabling them to concentrate on specific components of the workflow.
Both tracks will be evaluated on three few-shot and out-of-domain tasks on clinical data: infarct detection, meningioma segmentation, and brain age estimation.
No restrictions on fine-tuning method.
Both tracks will be evaluated on three few-shot and out-of-domain tasks on clinical data: infarct detection, meningioma segmentation, and brain age estimation.
No restrictions on fine-tuning method.
1️⃣: Train a model on FOMO-60K and competebest pretraining method.
2️⃣: Train a foundation model on any combination of data (both public and private) and showcase your foundation model with no restrictions.
1️⃣: Train a model on FOMO-60K and competebest pretraining method.
2️⃣: Train a foundation model on any combination of data (both public and private) and showcase your foundation model with no restrictions.
We release FOMO-60K, a large-scale dataset of 60,529 brain MRI from diverse set of resources, including clinical scans!
Dataset has been skull-stripped, co-registered and RAS-oriented, making it straightforward to start pretraining on.
Available on 🤗
We release FOMO-60K, a large-scale dataset of 60,529 brain MRI from diverse set of resources, including clinical scans!
Dataset has been skull-stripped, co-registered and RAS-oriented, making it straightforward to start pretraining on.
Available on 🤗