--- a
+++ b/dataset_description.md
@@ -0,0 +1,52 @@
+### Dataset Description
+
+CT Chest Segmentation Dataset.
+This dataset was be modified from `Lung segmentation dataset by Kónya et al., 2020 , https://www.kaggle.com/sandorkonya/ct-lung-heart-trachea-segmentation`
+
+The original nrrd files were re-saved in single tensor format with masks corresponding to labels: (**lungs**, **heart**, **trachea**) as numpy arrays using pickle.
+
+Each tensor has the following shape: number of slices, width, height, number of classes, where the width and height number of slices are individual parameters of each tensor id, and number of classes = 3.
+
+In addition, the data was re-saved as RGB images, where each image corresponds to one ID slice, and their mask-images have channels corresponding to three classes: (**lung**, **heart**, **trachea**).
+
+<p>
+  <img src="https://github.com/mandrakedrink/ChestCTSegmentation/blob/master/stats/data/demo.gif" width="35%" height="35%">
+</p>
+
+
+
+### Content
+**The dataset contains**:
+
++ numpy_images_files.zip - images in numpy format.
++ numpy_masks_files.zip  - segmentation masks in numpy format.
++ images.zip - images in RGB format.
++ masks.zip - segmentation masks in RGB format.
++ train.csv - csv file with image names.
+
+
+**Below is an example of what the data looks like:**
+
++ **.npy files can be readed like this:**
+
+```
+import pickle
+
+with open(file_path, 'rb') as f:
+    tensor = pickle.load(f)
+```
+
++ **The images look like this:**
+<p>
+  <img src="https://github.com/mandrakedrink/ChestCTSegmentation/blob/master/stats/data/svg/data_example2.svg" width="60%" height="60%">
+</p>
+
+<p>
+  <img src="https://github.com/mandrakedrink/ChestCTSegmentation/blob/master/stats/data/svg/data_example1.svg" width="60%" height="60%">
+</p>
+
+
+The code with  dataset  creation available here - [dataset_creation.ipynb](https://github.com/mandrakedrink/ChestCTSegmentation/blob/master/dataset_creation.ipynb)[<img src="https://colab.research.google.com/assets/colab-badge.svg" align="center">](https://colab.research.google.com/drive/166TOgOsRvcblQK2j_HTB8CmVy5VGabas?usp=sharing)
+
+
+---