From 9e1332b0ee3d831a2c105d2771b6c1533b36003f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9=20Pedersen?= Date: Tue, 10 Aug 2021 20:58:32 +0200 Subject: [PATCH] Update README.md --- README.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/README.md b/README.md index a3a7d0f..0172570 100644 --- a/README.md +++ b/README.md @@ -2,6 +2,7 @@ [![license](https://img.shields.io/github/license/DAVFoundation/captain-n3m0.svg?style=flat-square)](https://github.com/DAVFoundation/captain-n3m0/blob/master/LICENSE) [![GitHub Downloads](https://img.shields.io/github/downloads/SINTEFMedtek/GSI-RADS/total?label=GitHub%20downloads&logo=github)](https://github.com/SINTEFMedtek/GSI-RADS/releases) +[![Paper](https://zenodo.org/badge/DOI/10.1038/s41598-017-17204-5.svg)](https://doi.org/10.3390/cancers13122854) ![GSI-RADS](images/GSI-RADS_illustration.png) @@ -54,7 +55,6 @@ On **Windows** and **Ubuntu Linux** the software may be slow to start as it need * The cortical structures mask in original patient space for the different atlases used. * The input volume and tumor segmentation mask in MNI space in the sub-directory named \'registration\'. - ### 2.3 Computed features The following features are automatically computed and reported to the user: - **Multifocality**: whether the tumor is multifocal or not, the total number of foci, and the largest minimum distance between two foci. @@ -79,7 +79,6 @@ Then, to download the trained models locally, run the following: > python setup.py > deactivate - ### 3.2 Usage The command line input parameters are: * -g [--use_gui]: Must be set to 0 to disable the gui, otherwise 1. @@ -88,7 +87,6 @@ The command line input parameters are: * -o [--output_folder]: Main destination directory. A unique timestamped folder will be created inside for each run. * -d [--gpu_id]: Number of the GPU to use for the segmentation task. Set the value to -1 to run on CPU. - To run directly from command line, without the use of the GUI, run the following: > source venv/bin/activate > python main.py -g 0 -i /path/to/volume/T1.nii.gz -o /path/to/output/ -d 0