- ❤ We provide a comprehensive list of publications about 3D medical pre-training.
- 🔥 Welcome to share the paper and code through the issues.
| title | paper | repo |
|---|---|---|
| How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks? | link |  |
| MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset |  |
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| Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training |  |
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| CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection |  |
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| UniMiSS: Universal Medical Self-supervised Learning via Breaking Dimensionality Barrier |  |
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| Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis |  |
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| DoDNet: Learning to Segment Multi-Organ and Tumors from Multiple Partially Labeled Datasets |  |
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| Models Genesis |  |
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| Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis | |
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| VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis |  |
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| STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training |  |
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