Update README.md

README.md

@@ -64,7 +64,41 @@ To ensure consistency and quality, we only included MRI volumes with:
 - At least **32 slices per axis**
 - A resolution of **≤ 3×3×3 mm**
 
-Additionally we provide classification labels for 
+---
+
+## 📂 Dataset Folder Structure
+
+```text
+dataset/
+├── imagesTr_batch1/
+│   ├── BreastDivider_00001_0000.nii.gz
+│   ├── ...
+│   └── BreastDivider_10000_0000.nii.gz
+├── imagesTr_batch2/
+│   ├── BreastDivider_10001_0000.nii.gz
+│   ├── ...
+│   └── BreastDivider_17956_0000.nii.gz
+├── labelsTr_batch1/
+│   ├── BreastDivider_00001.nii.gz
+│   ├── ...
+│   └── BreastDivider_10000.nii.gz
+├── labelsTr_batch2/
+│   ├── BreastDivider_10001.nii.gz
+│   ├── ...
+│   └── BreastDivider_17956.nii.gz
+├── lesion_annotations/
+│   ├── classification/
+│   │   └── classification.csv
+│   └── segmentation/
+│       ├── DUKE_001.nii.gz
+│       ├── ...
+│       └── ISPY2_982505.nii.gz
+```
+
+- imagesTr_batch1 & imagesTr_batch2: Training images in .nii.gz format (split into two batches).
+- labelsTr_batch1 & labelsTr_batch2: Corresponding breast label masks in .nii.gz format (split into two batches).
+- lesion_annotations/classification: Contains classification.csv with 3021 lesion classification targets.
+- lesion_annotations/segmentation: Contains 467 lesion segmentation masks for bilateral images from the Mama Mia dataset.
 
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