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 ## Welcome to PyMIC 
 
-PyMIC is a pytorch-based toolkit for medical image computing with annotation-efficient deep learning. Despite that pytorch is a fantastic platform for deep learning, using it for medical image computing is not straightforward as medical images are often with high dimension and large volume, multiple modalities and difficulies in annotating. This toolkit is developed to facilitate medical image computing researchers so that training and testing deep learning models become easier. It is very friendly to researchers who are new to this area. Even without writing any code, you can use PyMIC commands to train and test a model by simply editing configuration files.  PyMIC is developed to support learning with imperfect labels, including semi-supervised and weakly supervised learning, and learning with noisy annotations.
+PyMIC is a Pytorch-based toolkit for medical image computing with annotation-efficient deep learning. Despite that pytorch is a fantastic platform for deep learning, using it for medical image computing is not straightforward as medical images are often with high dimension and large volume, multiple modalities and difficulies in annotating. This toolkit is developed to facilitate medical image computing researchers so that training and testing deep learning models become easier. It is very friendly to researchers who are new to this area. Even without writing any code, you can use PyMIC commands to train and test a model by simply editing configuration files.  PyMIC is developed to support learning with imperfect labels, including semi-supervised and weakly supervised learning, and learning with noisy annotations.
 
 Currently PyMIC supports 2D/3D medical image classification and segmentation, and it is still under development. It was originally developed for COVID-19 pneumonia lesion segmentation from CT images.