[ITK] [ITK-users] my problem
Dženan Zukić
dzenanz at gmail.com
Mon Jul 18 10:31:20 EDT 2016
The image you sent before is a 2D image, and you should do some 2D skull
stripping (e.g. this
<https://www.researchgate.net/publication/264042031_Skull_Stripping_of_MRI_Using_Clustering_and_2D_Region_Growing_Method>
).
Also, can you try to keep the conversation on the mailing list so other
people can benefit from it in the future?
Regards,
Dženan
On Mon, Jul 18, 2016 at 10:23 AM, meikolin saimara <kolin9105 at gmail.com>
wrote:
> thanks before sir,
> I have read this before but I don't about dataset.
> how about my image what I send before??
> can you remove the skull??
>
> On Mon, Jul 18, 2016 at 9:02 PM, Dženan Zukić <dzenanz at gmail.com> wrote:
>
>> 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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