[Insight-developers] dicom time series

[Iván Macía]

Hi,

We just filter the filenames according to the selected criteria. When the
image corresponds to a volume we use the standard itk::ImageSeriesReader by
passing it the filtered file names to create a 3D itk::Image. Otherwise, we
keep the filtered file names and read slice by slice on demand using
itk::ImageFileReader since usually on a time series we just need to show a
slice or a set of slices. I guess that in this case you can also use a 3D
itk::Image and interpret the third dimension as time, same with 4D.

Regards

Iván


-----Mensaje original-----
De: Richard Beare [mailto:richard.beare at gmail.com] 
Enviado el: domingo, 15 de febrero de 2009 7:31
Para: Ivan Macia
Asunto: Re: [Insight-developers] dicom time series

Hi,

I understand that part, but once you've figured out which slices
belong together, how do you assemble them into the volume or time
series in another format for subsequent processing, or don't you need
to do that?

On Sat, Feb 14, 2009 at 11:15 PM, Ivan Macia <imacia at vicomtech.org> wrote:
> Hi Richard,
>
> We decide ourselves based on Image Orientation Patient, Image Position
> Patient and some other tags as mentioned. For the latter tags we check for
> existance first.
> One good approach is to use a std::multimap as in gdcm::SerieHelper in
order
> to sort by IPP and check for duplicate positions. But sometimes (maybe not
> in your case) we have found intermixed volumes that need another kind of
> heuristic, such as checking a specific DICOM tag (i.e. Acquisition Group).
>
> In the case of MR 3D+t series, we checked for duplicate positions and
found
> let's say 4, and then we try to find a tag (among a set of predefined
tags)
> that varies among these images, like Temporal Position Identifier or Echo
> Time. Check one of the MR specific tags to see if it varies.
>
> HTH
>
> Iván
>
>
> 2009/2/14 Richard Beare <richard.beare at gmail.com>
>>
>> Hi,
>> I'll look into these tags.
>>
>> Do you reconstruct images using ITK once you've decided which dicoms
>> belong together, or use some other tool?
>>
>> On Fri, Feb 13, 2009 at 8:19 PM, Iván Macía <imacia at vicomtech.org> wrote:
>> > Dear Richard,
>> >
>> > In order to distinguish 3D images from 2D+t time series we usually
check
>> > Image Position Patient. Same Image Position Patient (and Image
>> > Orientation
>> > Patient of course) means it is a time series. I have not worked with MR
>> > Phase Contrast myself but other dynamic MR sequences (3D+t) from
Siemens
>> > have Temporal Position Identifier (0020,0100) and Number of Temporal
>> > Positions (0020,0105) DICOM tags. Note that these are optional.
>> > Otherwise,
>> > you may have a look at some other tags like Acquisition Time or
>> > Acquisition
>> > Group but usually it is difficult to find a rule that works for most
>> > vendors.
>> >
>> > DicomWorks software has a nice functionality that shows you which DICOM
>> > tags
>> > vary among the images of the same series so you can have a look to see
>> > if
>> > any of those is valid to identify the different groups you need.
>> >
>> > HTH
>> >
>> > Ivan
>> >
>> >
>> >
>> > -----Mensaje original-----
>> > De: insight-developers-bounces at itk.org
>> > [mailto:insight-developers-bounces at itk.org] En nombre de Richard Beare
>> > Enviado el: viernes, 13 de febrero de 2009 3:30
>> > Para: insight-developers at itk.org
>> > Asunto: [Insight-developers] dicom time series
>> >
>> > Hi,
>> > This question relates to the phase constrast dicom series I mentioned
>> > in my last post.
>> >
>> > These series are a time series of a single slice. My dicom sorting
>> > seems to be doing the right thing, but the conversion to nifti does
>> > not. The problem is that the time dimension is interpreted as the z
>> > dimension, so sequence appears as a 3d voume, rather than a 4d time
>> > series with a single slice. At present I'm not sure of the dimension
>> > figures that are being passed through the conversion process, so
>> > simply permuting the dimensions might not be advisable.
>> >
>> > Has anyone come across issues of this sort when reconstructing time
>> > series? Are there special dicom tags I'm likely to be missing?
>> >
>> > These are captured on a 1.5T siemens machine.
>> >
>> > Thanks
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>
>