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-#Summary
+# Summary
 
-Cellocity is an bioimage analysis tool for quantifying confluent cell dynamics written in Python. The main advantages of Cellocity is its ability work on unlabeled Brightfield time lapse microscopy data, and its ability to both quantify and visualize abstract optical flow analysis to the user. Cellocity aims to make optical flow based analysis of microscopy data accessible to a wide user base.
+Studying the coordinated movement of confluent cells can give insigths in to may different biological phenomena, such as wound healing, cancer metastasis, and host responses to bacterial infections. Such experiments can collectively be termend as confluent cell dynamics. Confluent cell dynamics is most often investigated by analyzing time lapse images generated by live cell microscopy. Thanks to recent developments in cell biology it is now possible to genereate tissue-like arrangements of primary cells, aslo known as organotypic culture. However, one disadvantage of such systems is that   
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+Analyzing brightfield microscopy time lapse images in order to study collective cell dynamics
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+# Statement of need
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+Cellocity is an bioimage analysis tool for quantifying confluent cell dynamics written in Python. The main advantages of Cellocity is its ability work on unlabeled Brightfield time lapse microscopy data, and its ability to both quantify and visualize abstract optical flow analysis to the user. Cellocity aims to make optical flow based analysis of microscopy data easier by providing a framework that keeps track of image metadata, performs common pre-processing steps, and implements previously published analysis algotithms. The architecture of Cellocity is designed to be highly customizable and modular. Implementing new analysis modules, image readers, and visualizations is straight forward with the help of Cellocity's developer guide and API.