Merge pull request #6 from hansenms/final_revisions

Final revisions

.gitignore

@@ -10,4 +10,7 @@ old
 *.aux
 *.fff
 *.lof
-*.h5
+*.h5
+code/ismrmrd_data/
+*.zip
+*_hash.tex

Makefile

@@ -0,0 +1,29 @@
+
+CURRENT_VERSION = ismrmrd_manuscript_mrm
+THE_GOAL	= ismrmrd_paper
+TARGETS		= $(THE_GOAL)
+
+SHA1 = $(shell git rev-parse HEAD)
+
+
+$(THE_GOAL).pdf: $(CURRENT_VERSION)_hash.tex
+	latex $(CURRENT_VERSION)_hash.tex
+	bibtex $(CURRENT_VERSION)_hash
+	latex $(CURRENT_VERSION)_hash.tex
+	latex $(CURRENT_VERSION)_hash.tex
+	dvipdf $(CURRENT_VERSION)_hash.dvi $(THE_GOAL).pdf
+
+$(CURRENT_VERSION)_hash.tex: $(CURRENT_VERSION).tex
+	sed -e s/MANUSCRIPT_SHA1/$(SHA1)/ $(CURRENT_VERSION).tex > $(CURRENT_VERSION)_hash.tex
+
+# so that when latex is re-run, it will get all references right
+
+update:
+	touch $(CURRENT_VERSION)_hash.tex
+
+really:
+	rm -f *.ps $(THE_GOAL).pdf $(CURRENT_VERSION).pdf
+
+clean:
+	rm -f *~ *.bbl *.blg *.pdf *.log *.aux *.bak *.dvi *.sav *.out *.nav *.snm *.toc *.fff *.lof $(CURRENT_VERSION)_hash.tex
+

README.md

@@ -0,0 +1,23 @@
+ISMRMRD Manuscript
+-------------------
+
+This repository contains the manuscript and associated example code for the ISMRM Raw Data format.
+
+If you have latex installed, you can generate a PDF of the manuscript with
+
+    $ make
+
+To run the example reconstructions:
+
+    $ cd code
+    $ ./doit.sh
+
+This will download the test data and run reconstructions (C++, Matlab, and Python).
+
+For all reconstructions to work, you must have:
+
+1. Compiled and installed ISMRMRD (https://github.com/ismrmrd/ismrmrd)
+2. Have added the path (``<ISMRMRD_SOURCE>/matlab``) to the Matlab API to your Matlab installation.
+3. Have installed the Python ISMRMRD API (https://github.com/ismrmrd/ismrmrd-python)
+
+On Windows computers or for individual steps (download and reconstructions), please see the ``code/doit.sh`` script for details.

code/do_clean.sh

@@ -0,0 +1,6 @@
+#!/bin/sh
+
+rm -f *.h5
+rm -f *.zip
+rm -rf ismrmrd_data
+

code/do_get_data.sh

@@ -4,7 +4,9 @@
 ismrmrd_generate_cartesian_shepp_logan -m 512 -o synth.h5
 
 # Copy the scanner data here
-cp ../data/*.h5 .
+wget https://github.com/ismrmrd/ismrmrd/releases/download/v1.2.3-data/ismrmrd_data.zip
+unzip ismrmrd_data.zip
+find ismrmrd_data -name "*.h5" -exec cp {} . \; -print
 
 
 

code/do_makefigs.py

@@ -3,14 +3,23 @@
 import ismrmrd
 import h5py
 
+def window_image(im,win_low=1,win_high=95):
+    imhist,bins = np.histogram(im.flatten(),100,normed=True)
+    im2 = im;
+    im2[im2 < bins[win_low]] = bins[win_low]
+    im2[im2 > bins[win_high]] = bins[win_high]
+    im2 = 255.0*(im2 - bins[win_low])/bins[win_high]
+    return im2
+
+
 fid = h5py.File('bruker.h5','r')
 bruk_cpp = np.squeeze(np.array(fid.get('/dataset/cpp/data')))
 bruk_mat = np.squeeze(np.array(fid.get('/dataset/matlab')))
 bruk_py  = np.squeeze(np.array(fid.get('/dataset/python')))
 fid.close()
-bruk_cpp *= 255/(0.9*np.max(bruk_cpp))
-bruk_mat *= 255/(0.9*np.max(bruk_mat))
-bruk_py  *= 255/(0.9*np.max(bruk_py))
+bruk_cpp = window_image(bruk_cpp)
+bruk_mat = window_image(bruk_mat)
+bruk_py = window_image(bruk_py)
 
 fid = h5py.File('ge.h5','r')
 ge_cpp = np.squeeze(np.array(fid.get('/dataset/cpp/data')))
@@ -19,38 +28,38 @@
 fid.close()
 # GE-data has chop so artifact at the edge of the image
 ge_cpp[0:1,:]=ge_cpp[2,:]
-ge_cpp *= 255/(0.9*np.max(ge_cpp))
+ge_cpp = window_image(ge_cpp,win_low=20,win_high=50)
 ge_mat[0:1,:]=ge_mat[2,:]
-ge_mat *= 255/(0.9*np.max(ge_mat))
+ge_mat = window_image(ge_mat,win_low=20,win_high=50)
 ge_py[0:1,:]=ge_py[2,:]
-ge_py  *= 255/(0.9*np.max(ge_py))
+ge_py = window_image(ge_py,win_low=20,win_high=50)
 
 fid = h5py.File('philips.h5','r')
 phil_cpp = np.squeeze(np.array(fid.get('/dataset/cpp/data')))
 phil_mat = np.squeeze(np.array(fid.get('/dataset/matlab')))
 phil_py  = np.squeeze(np.array(fid.get('/dataset/python')))
 fid.close()
-phil_cpp *= 255/(0.9*np.max(phil_cpp))
-phil_mat *= 255/(0.9*np.max(phil_mat))
-phil_py  *= 255/(0.9*np.max(phil_py))
+phil_cpp = window_image(phil_cpp,win_low=12,win_high=75)
+phil_mat = window_image(phil_mat,win_low=12,win_high=75)
+phil_py = window_image(phil_py,win_low=12,win_high=75)
 
 fid = h5py.File('siemens.h5','r')
 siem_cpp = np.squeeze(np.array(fid.get('/dataset/cpp/data')))
 siem_mat = np.squeeze(np.array(fid.get('/dataset/matlab')))
 siem_py  = np.squeeze(np.array(fid.get('/dataset/python')))
 fid.close()
-siem_cpp *= 255/(0.9*np.max(siem_cpp))
-siem_mat *= 255/(0.9*np.max(siem_mat))
-siem_py  *= 255/(0.9*np.max(siem_py))
+siem_cpp = window_image(siem_cpp,win_low=12,win_high=65)
+siem_mat = window_image(siem_mat,win_low=12,win_high=65)
+siem_py = window_image(siem_py,win_low=12,win_high=65)
 
 fid = h5py.File('synth.h5','r')
 syn_cpp = np.squeeze(np.array(fid.get('/dataset/cpp/data')))
 syn_mat = np.squeeze(np.array(fid.get('/dataset/matlab')))
 syn_py  = np.squeeze(np.array(fid.get('/dataset/python')))
 fid.close()
-syn_cpp = 255/(0.9*np.max(syn_cpp)) * syn_cpp[::-1,:]
-syn_mat = 255/(0.9*np.max(syn_mat)) * syn_mat[::-1,:]
-syn_py  = 255/(0.9*np.max(syn_py))  * syn_py[::-1,:]
+syn_cpp = window_image(syn_cpp)
+syn_mat = window_image(syn_mat)
+syn_py  = window_image(syn_py)
 
 w, h = 5.,3.
 dw, dh = 0.75, 0.4

code/do_recon_matlab.m

@@ -1,3 +1,8 @@
+% 
+% For this code to work, you must add <ISMRMRD_SOURCE>/matlab to your path
+% You also need to download the test data
+%      https://github.com/ismrmrd/ismrmrd/releases/download/v1.2.3-data/ismrmrd_data.zip
+%   
 function do_recon_matlab()
 
 fnames = {'synth.h5', 'bruker.h5', 'ge.h5', 'philips.h5', 'siemens.h5'};

code/do_recon_python.py

@@ -1,3 +1,10 @@
+#
+# In order to run this code, you must:
+# 1. Install the ismrmrd python api from:
+#     https://github.com/ismrmrd/ismrmrd-python
+# 2. Download the test data from https://github.com/ismrmrd/ismrmrd/releases/download/v1.2.3-data/ismrmrd_data.zip
+#
+
 import numpy as np
 from numpy.fft import fftshift, ifftshift, fftn, ifftn
 import ismrmrd

code/doit.sh

@@ -19,4 +19,4 @@ python do_makefigs.py
 mv *.eps ../figures
 
 # Clean up
-rm -f *.h5
+./do_clean.sh