realslimman
commited on
Commit
•
db21559
1
Parent(s):
a4b1531
Update README.md
Browse files
README.md
CHANGED
@@ -7,7 +7,15 @@ tags:
|
|
7 |
|
8 |
Welcome Medical Adapters Zoo!
|
9 |
|
10 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
|
12 |
Download an adapter for your target disease—trained on organs, lesions, and abnormalities—and effortlessly enhance SAM.
|
13 |
|
|
|
7 |
|
8 |
Welcome Medical Adapters Zoo!
|
9 |
|
10 |
+
## What
|
11 |
+
Here are the pre-trained Adapters to transfer SAM (Segment Anything Model) for segmenting various organs/lesions from the medical images.
|
12 |
+
|
13 |
+
## Why
|
14 |
+
|
15 |
+
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.
|
16 |
+
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.
|
17 |
+
Medical image segmentation includes many different organs, lesions, abnormalities as the targets.
|
18 |
+
So we are training different adapter for each of the target, and share them here for the easy usage in the community.
|
19 |
|
20 |
Download an adapter for your target disease—trained on organs, lesions, and abnormalities—and effortlessly enhance SAM.
|
21 |
|