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--- |
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license: apache-2.0 |
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pipeline_tag: image-segmentation |
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tags: |
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- medica |
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--- |
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Welcome Medical Adapters Zoo (Med-Adpt Zoo)! |
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## Med-Adpt Zoo Map 🐘🐊🦍🦒🦨🦜🦥 |
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Lung Nodule (CT) |
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Melanoma (Skin Photo) |
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OpticCup (Fundus Image) |
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OpticDisc (Fundus Image) |
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Thyroid Nodule (UltraSound) |
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Download the Adapters you need from [here](https://huggingface.co/KidsWithTokens/Medical-Adapter-Zoo/tree/main) |
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## What |
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Here are the pre-trained Adapters to transfer [SAM](https://segment-anything.com) (Segment Anything Model) for segmenting various organs/lesions from the medical images. |
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Check our paper: [Medical SAM Adapter](https://arxiv.org/abs/2304.12620) for the details. |
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## Why |
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SAM (Segment Anything Model) is one of the most popular open model for the image segmentation. Unfortaintly, it does not perform well on the medical images. |
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An efficient way to solve it is using Adapters, i.e., some layers with a few parameters to be added to the pre-trained SAM model to fine-tune it to the target down-stream tasks. |
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Medical image segmentation includes many different organs, lesions, abnormalities as the targets. |
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So we are training different adapter for each of the target, and share them here for the easy usage in the community. |
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Download an adapter for your target disease—trained on organs, lesions, and abnormalities—and effortlessly enhance SAM. |
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One adapter tranfers your SAM into a medical domain expert. Give it a try! |
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