Update README.md

README.md

@@ -104,14 +104,14 @@ Very simple demonstrations of the platform can be found on [Youtube](https://www
 
 ## 🎊 Features
 
-The software is implemented in C++ based on [FAST](https://github.com/smistad/FAST). A wide range of features have been added to the platform and FAST to make working with whole slide images (WSIs) a piece of cake!
+The software is implemented in C++ based using [FAST](https://github.com/smistad/FAST). A wide range of features have been added to make working with whole slide images (WSIs) a piece of cake!
 * **Graphical User Interface -** User-friendly GUI for working with WSIs without any code interaction.
 * **Deep learning -** Deployment and support for multi-input/output convolutional neural networks (CNNs).
 * **Visualization -** Real-time streaming of predictions on top of the WSI with low memory cost.
 * **Use cases -** Patch-wise classification, low and high-resolution segmentation, and object detection are supported.
 * **Inference Engines -** FAST includes a variety of different inference engines, i.e. TensorFlow CPU/CUDA (support both TF v1 and v2 models), TensorRT (UFF and ONNX), OpenVINO (CPU/GPU/VPU), and ONNX Runtime (CPU/GPU).
 * **Text pipelines -** Possibility to create your own pipelines using the built-in script editor.
-* **Formats -** Through OpenSlide FastPathology supports various WSI formats, as well as additional support for Olympus' CellSens VSI format through FAST.
+* **Formats -** Through OpenSlide FastPathology supports various WSI formats
 
 ## 🔬 Applications of FastPathology