license: afl-3.0
tags:
- medical
size_categories:
- 100M<n<1B
Dataset for AVS-Net Pre-training
The dataset utilized in the pre-training of the AVS-Net: Attention-based Variable Splitting Network for P-MRI Acceleration model, developed by Y Zhang, J Li, Z Wang, J Duan, and J Li, incorporates data from five distinct protocol sequences. These are:
- (coronal_pd)Coronal Spin Density-weighted without Fat Suppression
- (coronal_pd_fs)Coronal Spin Density-weighted with Fat Suppression
- (sagittal_pd)Sagittal Spin Density-weighted
- (sagittal_t2)Sagittal T2-weighted with Fat Suppression
- (axial_t2)Axial T2-weighted with Fat Suppression
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: Approximately 40 slices per protocol, each slice containing 15 channels, with a height and width (HW) of (640, 368)
```
knee_nyu
- axial_t2 coronal_pd(X) coronal_pd_fs sagittal_pd sagittal_t2
| | | | |
- [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12, 13, 14, 15, 16, 17, 18, 19, 20] masks
| |
- [train] [val]
| |
- 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.