From abf5c43de43668b85f4c049c95a8f1b7cf1d9f16 Mon Sep 17 00:00:00 2001 From: Guotai Wang Date: Thu, 16 Sep 2021 10:39:16 +0800 Subject: [PATCH] update readme, add myops --- README.md | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d0aa89e..ec004c9 100755 --- a/README.md +++ b/README.md @@ -34,7 +34,11 @@ Run the following command to install the current released version of PyMIC: ```bash pip install PYMIC ``` +To install a specific version of PYMIC such as 0.2.4, run: +```bash +pip install PYMIC==0.2.4 +``` Alternatively, you can download the source code for the latest version. Run the following command to compile and install: ```bash @@ -49,12 +53,15 @@ python setup.py install # Projects based on PyMIC Using PyMIC, it becomes easy to develop deep learning models for different projects, such as the following: -1, [COPLE-Net][coplenet] (TMI 2020), COVID-19 Pneumonia Segmentation from CT images. +1, [MyoPS][myops] Winner of the MICCAI 2020 myocardial pathology segmentation (MyoPS) Challenge. + +2, [COPLE-Net][coplenet] (TMI 2020), COVID-19 Pneumonia Segmentation from CT images. -2, [Head-Neck-GTV][hn_gtv] (NeuroComputing 2020) Nasopharyngeal Carcinoma (NPC) GTV segmentation from Head and Neck CT images. +3, [Head-Neck-GTV][hn_gtv] (NeuroComputing 2020) Nasopharyngeal Carcinoma (NPC) GTV segmentation from Head and Neck CT images. -3, [UGIR][ugir] (MICCAI 2020) Uncertainty-guided interactive refinement for medical image segmentation. +4, [UGIR][ugir] (MICCAI 2020) Uncertainty-guided interactive refinement for medical image segmentation. +[myops]: https://github.com/HiLab-git/MyoPS2020 [coplenet]:https://github.com/HiLab-git/COPLE-Net [hn_gtv]: https://github.com/HiLab-git/Head-Neck-GTV [ugir]: https://github.com/HiLab-git/UGIR