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  ## LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching (Neurips 2023).
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  We release [LVM-Med](https://arxiv.org/abs/2306.11925)'s pre-trained models and demonstrate downstream tasks on 2D-3D segmentations, linear/fully finetuning image classification, and object detection.
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  current contrastive and instance-based SSL.
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  <p align="center">
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- <img src="assets/body_lvm_med.jpg" alt="drawing" width="698.5" heigh="461"/>
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  </p>
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  <p align="center">
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- <img src="assets/lvm_med_teaser.gif" alt="drawing" width="471.6" heigh="520"/>
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  </p>
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  ## Table of contents
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  [//]: # (python train_segmentation.py -c ./dataloader/yaml_data/buid_endtoend_SAM_VIT.yml -test)
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- [//]: # (```)
 
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ pipeline_tag: feature-extraction
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+ tags:
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+ - medical
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+ ---
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  ## LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching (Neurips 2023).
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  We release [LVM-Med](https://arxiv.org/abs/2306.11925)'s pre-trained models and demonstrate downstream tasks on 2D-3D segmentations, linear/fully finetuning image classification, and object detection.
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  current contrastive and instance-based SSL.
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  <p align="center">
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+ <img src="assets/body_lvm_med.jpg" alt="drawing" width="650"/>
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  </p>
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  <p align="center">
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+ <img src="assets/lvm_med_teaser.gif" alt="drawing" width="800"/>
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  </p>
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  ## Table of contents
 
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  [//]: # (python train_segmentation.py -c ./dataloader/yaml_data/buid_endtoend_SAM_VIT.yml -test)
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+ [//]: # (```)