Update README.md

README.md

@@ -19,10 +19,12 @@ The dataset utilized in the pre-training of the AVS-Net: Attention-based Variabl
 
 The dataset is structured on a slice-by-slice basis, with each slice containing 20 cases. Each case is comprised of two files: rawdata*.mat and espirit*.mat. The dataset's structure can be outlined as follows:
 
-## Dataset: /rds/projects/d/duanj-ai-in-medical-imaging/knee_nyu
-### Protocol: [coronal_pd, coronal_pd_fs, sagittal_pd, sagittal_t2, axial_t2]
 
-Dataset architecture:
+## Dataset architecture:
+
+- name: /rds/projects/d/duanj-ai-in-medical-imaging/knee_fast_mri
+- Protocol: [coronal_pd, coronal_pd_fs, sagittal_pd, sagittal_t2, axial_t2]
+
 Approximately 40 slices per protocol, each slice containing 15 channels, with a height and width (HW) of (640, 368)
 
     ```
@@ -36,4 +38,14 @@ Approximately 40 slices per protocol, each slice containing 15 channels, with a
         - espirit*.mat(1-40), rawdata*.mat(1-40)                       *_masks.mat
     ```
 
-In this structure, each protocol has approximately 40 slices, each consisting of 15 channels. The dimensions of the data are 640x368 (height x width). For each protocol, the slices are further divided into two groups: the training set ([train]) and the validation set ([val]). The training set includes the espirit*.mat and rawdata*.mat files for each slice, while the validation set contains *_masks.mat files.
+In this structure, each protocol has approximately 40 slices, each consisting of 15 channels. The dimensions of the data are 640x368 (height x width). For each protocol, the slices are further divided into two groups: the training set ([train]) and the validation set ([val]). The training set includes the espirit*.mat and rawdata*.mat files for each slice, while the validation set contains *_masks.mat files.
+
+## Dataset Usage
+
+> For a standalone knee dataset download, use `git lfs`(<https://git-lfs.com/>) to download from the `huggingface` datasets(<https://huggingface.co/datasets/AVS-Net/knee_coronal_pd>):
+
+```bash
+# Make sure you have git-lfs installed (https://git-lfs.com)
+git lfs install
+git clone -j8 [email protected]:datasets/AVS-Net/knee_fast_mri
+```