update readme

Author: taigw

README.md

@@ -1,19 +1,17 @@
 # SimpleCRF
 Matlab and Python wrap of Conditional Random Field (CRF) and fully connected (dense) CRF for 2D and 3D image segmentation, according to the following papers:
 
-[1] Yuri Boykov and Vladimir Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision", in IEEE TPAMI, 2004.
-
-Pushmeet Kohli and Philip H.S. Torr. "Efficiently solving dynamic markov random fields using graph cuts", ICCV, 2005
+[1] Yuri Boykov and Vladimir Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision", IEEE TPAMI, 2004.
 
 [2] Philipp Krähenbühl and Vladlen Koltun, "Efficient inference in fully connected crfs with gaussian edge potentials", in NIPS, 2011.
 
-[3] Kamnitsas et al. "Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI", in Proceeding of ISLES challenge, MICCAI, 2015.
+[3] Kamnitsas et al in "Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation", Medical Image Analysis, 2017.
 
 ![maxflow](./data/maxflow.png)
 ![densecrf1](./data/densecrf1.png)
 ![densecrf2](./data/densecrf2.png)
 
-# Dependency
+### Dependency
 This repository depends on the following packages:
 
 * Maxflow  https://vision.cs.uwaterloo.ca/code/ 
@@ -22,7 +20,16 @@ This repository depends on the following packages:
 
 * 3D Dense CRF https://github.com/deepmedic/dense3dCrf
 
-# Examples
+### Installation
+1. Install with pip: [`pip install SimpleCRF`][https://github.com/taigw/SimpleCRF]
+
+2. Alternatively, you can compile the source files by the following two steps:
+```bash
+python setup.py build
+python setup.py install
+```
+
+### Examples
 Some demos of using this package are:
 
 * `examples/demo_maxflow.py`: using maxflow for automatic and interactive segmentation of 2D and 3D images.
@@ -31,22 +38,24 @@ Some demos of using this package are:
 
 * `examples/demo_densecrf3d.py`: using 3D dense CRF for 3D multi-modal image segmentation.
 
-# Modules
-1, `maxflow` has four functions as follows. Note that the current version only supports binary segmentation.
+### Modules
+1. `maxflow` has four functions as follows. Note that the current version only supports binary segmentation.
+
+* `maxflow.maxflow2d()` for 2D automatic segmentation.
+
+* `maxflow.interactive_maxflow2d()` for 2D interactive segmentation.
 
-* maxflow.maxflow2d() for 2D automatic segmentation.
+* `maxflow.maxflow3d()` for 3D automatic segmentation.
 
-* maxflow.interactive_maxflow2d() for 2D interactive segmentation.
+* `maxflow.interactive_maxflow3d()` for 3D interactive segmentation.
 
-* maxflow.maxflow3d() for 3D automatic segmentation.
+2. `denseCRF` has the following function. It can deal with multi-class segmentation, and only supports RGB images.
 
-* maxflow.interactive_maxflow3d() for 3D interactive segmentation.
+* `denseCRF.densecrf()` for 2D automatic segmentation.
 
-2, `denseCRF` has the following function. It can deal with multi-class segmentation, and only supports RGB images.
+3. `denseCRF3D` has the following function. It can deal with multi-class segmentation. The input channel number can be 1-5.
 
-* denseCRF.densecrf() for 2D automatic segmentation.
+* `denseCRF3D.densecrf3d()` for 3D automatic segmentation.
 
-2, `denseCRF3D` has the following function. It can deal with multi-class segmentation, and the input channel number can be 1-5.
 
-* denseCRF3D.densecrf3d() for 3D automatic segmentation.