README.md

---
language:
- en
license: mit
task_categories:
- image-feature-extraction
tags:
- slam-microscopy
size_categories:
- 1GB<n<10GB
---

# Dataset Name: Mouse Brain SLAM (simultaneous label-free autofluorescence-multiharmonic microscopy) Images

This dataset contains multimodal microscopy imaging data, including 4-channel SLAM images, THG anisotropy data, and corresponding regional annotations/label maps.

## 📂 Data Hierarchy & Naming Convention

Each dataset folder follows the naming convention:
`[mouse model]_[orientation]_[age]_[acquisition date]`

### Folder Contents
For every acquisition, the following files are provided:

| File Name | Description |
| :--- | :--- |
| `dslam_4channel.tif` | **Raw Data:** 4-channel SLAM image. |
| `dslam_4channel.png` | **Preview:** RGB visualization of the 4-channel SLAM data. |
| `thg_polarization.tif` | **Raw Data:** Third Harmonic Generation (THG) anisotropy/polarization image. |
| `dslam_4channel_upsampled_label_map.npy` | **Annotation:** High-resolution spatial label map (NumPy array). |
| `dslam_4channel_upsampled_label_map.json` | **Metadata:** Annotation parameters and label mapping information. |
| `dslam_4channel_upsampled_label_map.png` | **Visual Reference:** Color-coded version of the label map. |

### Regional Masks Subdirectory (`/regional_masks`)
Specific regions of interest (ROIs) are separated into individual mask files:
* `region_mask_metadata.json`: Metadata defining the regions and acquisition parameters.
* `mask_[region_name].npy`: Binary/categorical spatial data for a specific region.
* `mask_[region_name].tif`: High-bit depth image representation of the specific regional mask.

---

## 🛠 Usage & Loading

### Prerequisites