[ITK] [ITK-users] my problem
Dženan Zukić
dzenanz at gmail.com
Mon Jul 18 10:02:55 EDT 2016
There is a paper
<http://www.insight-journal.org/download/viewpdf/859/4/download> which goes
along with the source code, which give more description as well as how to
call the filter.
On Mon, Jul 18, 2016 at 9:55 AM, meikolin saimara <kolin9105 at gmail.com>
wrote:
> I just have tried how to compile the code. I am confused how to use it.
>
> but I have problem to use that because the skull stripping approaches need
> data sheet of brain.
> I just want send one image in my thesis no more.
> I am sorry sir I am beginner in ITK.
>
>
> On Mon, Jul 18, 2016 at 8:02 PM, Dženan Zukić <dzenanz at gmail.com> wrote:
>
>> Have you tried some skull stripping approaches? One example is this:
>> http://www.insight-journal.org/browse/publication/859
>>
>> Also, something similar to what you are trying to do already exists:
>> http://volbrain.upv.es
>>
>> Regards
>>
>> On Mon, Jul 18, 2016 at 4:34 AM, meikolin saimara <kolin9105 at gmail.com>
>> wrote:
>>
>>> oke I will explain to you what I want to do in my thesis.
>>> in my thesis I want to build web service to analyze large of brain tumor.
>>> the steps are client send one image of brain which one will be analyzed
>>> after that server will be processed the image without being noticed by
>>> client.
>>> in server using command prompt to analyzed the image. after that the
>>> result will be showed to Client.
>>>
>>> now my problem is I can't remove outside the skull with itk in my server.
>>> if outside the skull Can't be removed so the itk program will enter
>>> pixel of the skull mixed the tumor.
>>> first image is before processed and second image is after processed.
>>> in confidence connected uses the seedX is 100 and the seedY 75.
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> On Fri, Jul 15, 2016 at 9:34 PM, Dženan Zukić <dzenanz at gmail.com> wrote:
>>>
>>>> Hi Meikolin,
>>>>
>>>> it is not clear to me what your problem is. Can you give some images
>>>> (what you get, what you want, where you put the seeds) and explain a bit
>>>> more what you did code-wise? Otherwise I would have to guess.
>>>>
>>>> Regards,
>>>> Dženan
>>>>
>>>> On Fri, Jul 15, 2016 at 3:26 AM, meikolin saimara <kolin9105 at gmail.com>
>>>> wrote:
>>>>
>>>>> thanks before sir..
>>>>> I have one problem in my thesis.
>>>>> I have a image of brain tumor,I can find the tumor and the skull using
>>>>> confidence connected segmentation, but I just wanna need the tumor no the
>>>>> skull. I just wanna one picture no full head to analyzed.
>>>>> can you help me sir??
>>>>> please sir..
>>>>>
>>>>> On Fri, Jul 15, 2016 at 3:54 AM, Dženan Zukić <dzenanz at gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Hi Meikolin,
>>>>>>
>>>>>> there is no "advantage" to seeds, it is how confidence connected
>>>>>> filter operates. It finds all voxels which are connected to the provided
>>>>>> seeds with a certain confidence. So seeds are starting points.
>>>>>>
>>>>>> Regards,
>>>>>> Dženan
>>>>>>
>>>>>> On Thu, Jul 14, 2016 at 1:49 PM, meikolin saimara <
>>>>>> kolin9105 at gmail.com> wrote:
>>>>>>
>>>>>>> hello every one I am so confused until now I haven't find the
>>>>>>> correct answer about , what is the advantage seedX and seedY in
>>>>>>> confidence connected filter ???
>>>>>>>
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>>>>>>
>>>>>
>>>>
>>>
>>
>
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