refactor: update README

Author: Aditya Wardianto

README.md

@@ -1,31 +1,37 @@
-# UNET++ based CAC Scoring
+# Mobile UNet++ Model for Coronary Artery Calcium Scoring
+
 **THIS REPO IS STILL UNDER DEVELOPMENT, IMPROVEMENT IS WELCOMED!**
 
-A UNet++ based ML model to do automatic CAC scoring
+A UNet++ with MobileNetv2 block based ML model to do automatic CAC scoring
 This is a repo to develop my Undergraduate Thesis on Biomedical Engineering
 
 ### Development Environment
+
 - WSL2 Ubuntu Linux 20.04.4 LTS
 - Miniconda (for environment management)
 - Poetry (for dependencies management)
-- Python 3.9.12
+- Python 3.10.8
 
 ### Library
+
 - Tensorflow
 - Streamlit
-- Pydicom
+- PyDicom
 - Numpy
 
 ### Reference
+
 - Paper:
   - [Original Paper using COCA Dataset (they use UNET Architecture)](https://www.nature.com/articles/s41746-021-00460-1)
   - [Calcium Scoring Method](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487233/)
 - Code:
-  -  [keras-unet-collection](https://github.com/yingkaisha/keras-unet-collection)
+  - [keras-unet-collection](https://github.com/yingkaisha/keras-unet-collection)
+  - [azcopy install script](https://gist.github.com/aessing/76f1200c9f5b2b9671937b3b0ed5fd6f)
 
 # Dataset
-The dataset used for this model is provided by Stanford AI COCA Dataset, this dataset can be accessed through this [link](https://stanfordaimi.azurewebsites.net/datasets/e8ca74dc-8dd4-4340-815a-60b41f6cb2aa.)
+
+The dataset used for this model is provided by Stanford AI COCA Dataset, this dataset can be accessed through this [link](https://stanfordaimi.azurewebsites.net/datasets/e8ca74dc-8dd4-4340-815a-60b41f6cb2aa)
 
 This model is using Gated MRI Data from the COCA Dataset consisting of the MRI image saved in a DICOM format and the calcium mask saved in a xml plist format.
 
-Other dataset usage will be developed after the implementation of the COCA Dataset has been done.
+Other dataset usage will be developed after the implementation of the COCA Dataset has been done.