minor edit

README.md

@@ -1,4 +1,4 @@
-# **Vessel Boost**
+# **VesselBoost**
 *VesselBoost* is a Python-based software package utilizing deep learning techniques to segment high-resolution time-of-flight MRI angiography data, with high sensitivity towards small vessels. The software suite encompasses three essential functional modules: (1) *predict*, (2) *test-time adaptation* (TTA), and (3) *boost*. By leveraging these modules, users can efficiently segment high-resolution time-of-flight data or conveniently leverage our command line interface to boost segmentations for other vascular MRI image contrasts.
 
 ## **Table of Contents**
@@ -16,7 +16,7 @@ This repository contains 3 major modules:
 
 1. [Predict](https://github.com/KMarshallX/vessel_code/blob/master/documentation/predict_readme.md). With this module, users can segment high-resolution time-of-flight using our pre-trained models. It can be used to generate intermediate proxy segmentations as well as the final ones.
 2. [Test-time-adaptation](https://github.com/KMarshallX/vessel_code/blob/master/documentation/tta_readme.md). This module allows the user to provide a proxy segmentation or generate a proxy with our pre-trained model (Module 1), to drive further adaptation of the pre-trained models.
-3. [Boost](https://github.com/KMarshallX/vessel_code/blob/master/documentation/boost_readme.md). *Boost* allows users to train a segmentation model on a single or more data using existing imperfect segmentation.
+3. [Booster](https://github.com/KMarshallX/vessel_code/blob/master/documentation/boost_readme.md). *Boost* allows users to train a segmentation model on a single or more data using existing imperfect segmentation.
 
 <p align="center">
 <img src="./paper/figure1.png">