[Rtk-users] Rooster

[Cyril Mory]

Hi Guillaume,

Just wanted to let you know : if you perform a 4D CT for the planning, 
and use motion estimation on that 4D CT (thus getting either one 4D 
displacement vector field, or two inverse-consistent 4D DVFs), you can 
use this/these DVF(s) in ROOSTER. It should bring you a significant 
improvement of image quality, and on my datasets I was able to reduce 
the number of iterations of the main loop to 10 without problems.

We can discuss this further if you are interested.
Cyril

On 06/01/2016 09:44 AM, Cyril Mory wrote:
> The bottleneck is the 4D conjugate gradient, and by far. You can also 
> try to reduce the number of main loop iterations (10 should already 
> give a nice result, but you may need more for your application).
> That, plus reducing the size of your reconstructed volume, plus the 
> optimizations I'm working on, should give you a reconstruction time of 
> less than one hour.
>
> On 06/01/2016 09:39 AM, Guillaume Landry wrote:
>> Good morning Cyril,
>>
>> Thanks for answering, yes I used 1.2.0. I did 30 main iterations, 4 CG
>> and 10 for TV (taken from example). Possibly I could reduce the number
>> of TV iterations?
>>
>> Looking forward to your optimizations.
>>
>> Cheers
>> Guillaume
>>
>> Dr. Guillaume Landry
>> Ludwig Maximilians University (LMU) Munich
>> Medical Physics
>> Am Coulombwall 1
>> 85748 Garching
>> Tel:+49 (0) 89 289-14077
>> Fax:+49 (0) 89 289-14072
>>
>> On 06/01/2016 09:34 AM, Cyril Mory wrote:
>>> Hi Guillaume,
>>>
>>> Can you also tell how many iterations you have performed (main loop,
>>> conjugate gradient, and TV) ?
>>> If you are performing 30 iterations of the main loop, with 4 CG
>>> iterations, then considering the size of your data I do not think
>>> anything is wrong. Reconstructing a smaller volume will give you a
>>> large speedup (time is almost linear with number of voxels), so I
>>> would recommend that you try again with the smallest possible volume,
>>> i.e. the bounding box of your patient.
>>>
>>> Are you running the release 1.2.0 version ? If so, note that on the
>>> master branch of the git repository, I am adding optimizations for the
>>> 4D reconstructions. It is not fully functional at the moment, but I'm
>>> currently working 100% of my time on it. I will let you know about the
>>> next updates.
>>>
>>> Regards,
>>> Cyril
>>>
>>> On 05/31/2016 07:48 PM, G.Landry at physik.uni-muenchen.de wrote:
>>>> Hi Simon,
>>>>
>>>> Thanks for mailing list suggestion. My initial question was about
>>>> typical reconstruction times for rtkfourdrooster. What I tried is
>>>> summarized below:
>>>>
>>>> -Volume size was 410 410 264 and could be easily reduced by a good
>>>> margin.
>>>>
>>>> -The GPU is quadro M4000 with 8GB
>>>>
>>>> -about 2300 256x256 projections with shifted elekta panel (so called
>>>> M20)
>>>>
>>>> -10 phases
>>>>
>>>> -for the motion mask at the moment I just used the FOV mask for first
>>>> try.
>>>>
>>>> --gamma_time 0.0001
>>>> --gamma_space 0.0001
>>>> - spacing 1 1 1
>>>> --niter 30
>>>> --cgiter 4
>>>> --tviter 10
>>>>
>>>>
>>>> Recon time was about 5-6 hours. I saw about 4 Gb used on the card.
>>>>
>>>> The image looked nice, albeit with the TV "feel/plastic-y".
>>>>
>>>> Thanks for your feedback
>>>> Guillaume
>>>>
>>>>
>>>>
>>>>
>>>> Quoting Simon Rit <simon.rit at creatis.insa-lyon.fr>:
>>>>
>>>>> Hi Guillaume,
>>>>> I'm adding RTK user list to this conversation, it's better to have
>>>>> these conversations on the mailing list IMO. Can you tell us what's
>>>>> the volume size and the GPU?
>>>>> Cyril is ROOSTER's dev, maybe he could comment on recon times.
>>>>> Simon
>>>>>
>>>>> On Tue, May 31, 2016 at 5:29 PM, <G.Landry at physik.uni-muenchen.de>
>>>>> wrote:
>>>>>> Hi Simon,
>>>>>>
>>>>>> I tried the rooster recon. I used the parameters from the example
>>>>>> page. The results looks rather nice but it took several hours to
>>>>>> run (5-6). Its a big dataset of about 2000 256x256 projections.
>>>>>>
>>>>>> Guillaume
>
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