Jan 042010
There is a great Python package pydicom that implements a nice interface in order to be able to access data within Dicom files.
One application which I wrote up was a dicom directory summarizer which goes through a list of dicom files and summarizes the types of MRI data in the directory. I found myself getting frustrated trying to figure out which series of data was which given the huge number of dicom files (with really long names too!) in a directory.
The code below may be run within a Dicom directory and should run on Siemens Dicom data (IMA) files. It has been a while that I have run it so I can’t guarantee that it will work, but it should be a good place to start.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | #! /usr/bin/python import dicom import os import re def blah(val): return re.compile('[\-\w]+\.MR\.[\-\w]+\.\d+\.1\..*').match(val, 1) # Get a list of all the files files = [] for entry in os.listdir('.'): if ~os.path.isdir(entry) & entry.endswith('IMA'): files.append(entry) # Filter to find the first of each series firsts = filter( blah, files ) firsts.sort(key=lambda s: int( re.compile('[\-\w]+\.MR\.[\-\w]+\.(\d+)\.1\..*').search(s).group(1)) ) # Read the first and output some interesting stuff d = dicom.ReadFile(firsts[1]) print " Patient: " + d.PatientsName print "Acquired: " + d.StudyDate[0:4]+"-"+d.StudyDate[4:6]+"-"+d.StudyDate[6:8] \ + " " + d.StudyTime[0:2] + ":" + d.StudyTime[2:4] + ":" + d.StudyTime[4:6] print "Comments: " + d.ImageComments # Run through the first file of each of the series for entry in firsts: d = dicom.ReadFile(entry) num = re.compile('[\-\w]+\.MR\.[\-\w]+\.(\d+)\.1\..*').search(entry).group(1) out = "\t" + str(num) + ") " + d.SeriesDescription tt = '[_\-\w]+\.MR\.[_\-\w]+\.'+str(num)+'\..*' count = 0 r = re.compile(tt) for f in files: if( r.match(f, 1) ): #print "%s matches %d" % (f, ii) count = count + 1 if( not re.compile(".*(FA|TRACEW|TENSOR|ADC|MoCoSeries)$").match(d.SeriesDescription, 1 ) ): out += " (vols=" + str(count) if( 'RepetitionTime' in d ): out += ", TR=" + str(d.RepetitionTime) if( 'EchoTime' in d ): out += ", TE=" + str(d.EchoTime) out += ")" print out |
Have you heard of quickdicom?
http://sourceforge.net/projects/quickdicom/
This toolkit was made in our lab (imaginginformatics.ca) and is super-useful for mac. Once this toolkit is installed Finder understands dicom files – so you can see thumbnails of the files as well as the dicom header, meaning that spotlight can search dicom headers. You can double-click dicom file sand quickdicom acts as a dicom viewer with standard viewing options like window/level. Included in the package is a framework that can be used by Objective C or Python.
Another feature I found quite by accident is that quickdicom’s window/level function becomes available to pixelmator. I often use this filter now to quickly touch-up photos.
Cheers!
I haven’t heard of it before but I’ll try it out. I don’t typically use Dicom images here but I’ll keep it in mind if I hear others need this type of thing. Thanks!