RawWriterType;
FileSinkType::Pointer fileSink = FileSinkType::New();
RawWriterType::Pointer rawWriter = RawWriterType::New();
rawWriter->SetDimensions( 0, nx );
rawWriter->SetDimensions( 1, ny );
fileSink->SetImageIO( rawWriter );
fileSink->SetFileName( outputFileName );
fileSink->SetInput( image1);
try
{
fileSink->Write();
}
catch( itk::ExceptionObject & e )
{
std::cerr << "Exception caught during Raw file writing " << std::endl;
std::cerr << e << std::endl;
return -1;
}
std::cout << "File succesfully writen ! " << std::endl;
return 0;
}
Thanking you,
Regards,
Ramakrishna
------_=_NextPart_001_01C234A8.41B123CE
Content-Type: text/html;
charset="iso-8859-1"
You haven't set
the elements in the structuring element. So you are dilating with a
structuring
element that only
has zeros.
Try using an
itk::BinaryBallStructuringElement as your structuring element. This will
allow
you to dilate
with a ball (ellipsoid) of prescribe radii.
Take a look at
Insight/Code/Testing/BasicFilters/itkBinaryDilateImageFilterTest.cxx to
see
how to setup a
structuring element.
Dear Mr.Bjorn and Friends,
I am working on Dilation of a image.But I am not
getting any effect on o/p.What ever I/P I have given it is
giving same
o/p.There is no difference.Where exactly I am doing wrong.Please
give me
suggestion.I have written code as follows.
int main()//(int argc, char
**argv)
{
const char * inputFileName
="100";// argv[1];
const char * outputFileName ="output";//
argv[4];
const unsigned int nx = 256;//atoi(
argv[2] );
const unsigned int ny = 256;//atoi( argv[3]
);
typedef unsigned
short PixelType;
const unsigned
int Dimension = 2;
typedef itk::Image< PixelType,
Dimension > ImageType;
// Read
a Raw File
typedef itk::ImageFileReader< ImageType
> FileSourceType;
typedef
itk::RawImageIO<PixelType,Dimension>
RawReaderType;
FileSourceType::Pointer fileSource =
FileSourceType::New();
fileSource->SetFileName( inputFileName
);
RawReaderType::Pointer rawReader =
RawReaderType::New();
rawReader->SetDimensions( 0, nx
);
rawReader->SetDimensions( 1, ny );
fileSource->SetImageIO( rawReader );
try
{
fileSource->Update();
}
catch( itk::ExceptionObject & e )
{
std::cerr << "Exception caught during Raw file
reading " << std::endl;
std::cerr << e
<< std::endl;
return -1;
}
std::cout << "File succesfully read ! " <<
std::endl;
ImageType::Pointer image =
fileSource->GetOutput();
//Dialate Erode
itk::Size<2> size = {256, 256};
typedef
itk::NeighborhoodAllocator<PixelType>
NAllocator;
NAllocator *nat=new
NAllocator;
typedef
itk::Neighborhood<PixelType,(unsigned int)2,NAllocator>
KernelType;
KernelType *NA=new
KernelType;
std::cout<<"Radius(Input)
"<<size;
NA->SetRadius(size);
unsigned short
cv=NA->GetCenterValue();
std::cout<<"\ncenter
value"<<" "<<cv<<"\n";
std::cout<<"\nRadius of the neighborhood
"<<NA->GetRadius();
std::cout<<"\nRadius
along a two dimension "<<NA->GetRadius((const unsigned
long)2);
std::cout<<"\nRadius along a one
dimension "<<NA->GetRadius((const unsigned
long)1);
std::cout<<"\n\nsize (total length of
sides) of the neighborhood "<<NA->GetSize();
unsigned long size2=NA->GetSize((const unsigned
long)2);
unsigned long size1=NA->GetSize((const
unsigned long)1);
std::cout<<"\nsize2(along a two
dimension) "<<" "<<size2<<"\nsize1(one
dimension) "<<size1;
typedef
itk::BinaryDilateImageFilter<ImageType,ImageType,KernelType>
Morphology;
Morphology::Pointer GMF=
Morphology::New();
GMF->SetInput(image);
GMF->SetDilateValue(25000);
ImageType::Pointer image1 = GMF->GetOutput();
//
Write a Raw File
typedef itk::ImageFileWriter< ImageType
> FileSinkType;
typedef
itk::RawImageIO<PixelType,Dimension> RawWriterType;
FileSinkType::Pointer fileSink =
FileSinkType::New();
RawWriterType::Pointer rawWriter =
RawWriterType::New();
rawWriter->SetDimensions( 0, nx );
rawWriter->SetDimensions( 1, ny );
fileSink->SetImageIO(
rawWriter );
fileSink->SetFileName( outputFileName );
fileSink->SetInput( image1);
try
{
fileSink->Write();
}
catch(
itk::ExceptionObject & e )
{
std::cerr << "Exception caught during Raw file writing " <<
std::endl;
std::cerr << e <<
std::endl;
return -1;
}
std::cout << "File succesfully writen ! " << std::endl;
return 0;
}
Thanking you,
Regards,
Ramakrishna
------_=_NextPart_001_01C234A8.41B123CE--
From salah@gris.uni-tuebingen.de Fri Jul 26 15:11:50 2002
From: salah@gris.uni-tuebingen.de (Zein Salah)
Date: Fri, 26 Jul 2002 16:11:50 +0200
Subject: [Insight-users] Fw: simple example of using any segmentation filter
Message-ID: <010301c234ae$6282ac40$aeb00286@wsigris.unituebingen.de>
This is a multi-part message in MIME format.
------=_NextPart_000_0100_01C234BF.25FD2460
Content-Type: text/plain;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Hi all,
The SimpleFuzzyConnectednessScalarImageFilter works for a long time and =
produces just a black volume image, i.e. nothing at all can be seen.
has anybody an idea where is the problem
thanks,
Zein
----- Original Message -----=20
From: Zein Salah=20
To: ITK Users=20
Sent: Friday, July 26, 2002 2:48 PM
Subject: Fw: simple example of using any segmentation filter=20
Hello ITK users,
I have build a segmentation program that uses the=20
ConnectedThresholdImageFilter
on raw images that are read using MetaImageIO... and it worked.=20
I tried to apply the same method with the=20
IsolatedConnectedImageFilter as well as with the =
SimpleFuzzyConnectednessScalarImageFilter
the program went in an infinite loop.=20
I realy do not know waht should the problem be.=20
1. Do not these filters work with volume data????
2. if they do, what are the parameters to be set?? to what values??
Thanks in advance for any kind of help.
zein
->8<------------->8<------------->8<------------->8<------------->8<-----=
-------->8<-
Zein I. Salah=20
Universit=E4t T=FCbingen, WSI-GRIS=20
Sand 14=20
72076 T=FCbingen=20
Email: salah@gris.uni-tuebingen.de / zeinsalah@hotmail.com
Tel.: (07071) 29 75465 (GRIS) , (07071) 96 44 39 (privat)=20
------=_NextPart_000_0100_01C234BF.25FD2460
Content-Type: text/html;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Hi all,
The SimpleFuzzyConnectednessScalarImageFilter works =
for a=20
long time and produces just a black volume image, i.e. nothing at all =
can be=20
seen.
has anybody an idea where is the =
problem
thanks,
Zein
----- Original Message -----=20
Sent: Friday, July 26, 2002 2:48 PM
Subject: Fw: simple example of using any segmentation filter =
Hello ITK users,
I have build a segmentation =
program that uses=20
the
on raw images that are read using=20
MetaImageIO... and it worked.
I tried to apply the same method with =
the=20
IsolatedConnectedImageFilter as well as =
with the=20
SimpleFuzzyConnectednessScalarImageFilter
the program went in an infinite loop. =
I realy do not know waht should the =
problem be.=20
1. Do not these filters work with =
volume=20
data????
2. if they do, what are the parameters =
to be set??=20
to what values??
Thanks in advance for any kind of=20
help.
zein
->8<------------->8<------------->8<----------=
--->8<------------->8<------------->8<-
Zein=20
I. Salah
Universit=E4t T=FCbingen, WSI-GRIS
Sand 14
72076 =
T=FCbingen=20
Email: salah@gris.uni-tuebingen.de =20
/ zeinsalah@hotmail.com
Tel.: =
(07071) 29 75465 (GRIS) , (07071) 96 44 39 (privat) =
------=_NextPart_000_0100_01C234BF.25FD2460--
From yj76@columbia.edu Fri Jul 26 15:31:30 2002
From: yj76@columbia.edu (Yinpeng Jin)
Date: Fri, 26 Jul 2002 10:31:30 -0400
Subject: [Insight-users] Fw: simple example of using any segmentation filter
References: <010301c234ae$6282ac40$aeb00286@wsigris.unituebingen.de>
Message-ID: <002901c234b1$2212d330$3e483b80@segment>
This is a multi-part message in MIME format.
------=_NextPart_000_0026_01C2348F.9ABE5DD0
Content-Type: text/plain;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
SimpleFuzzyConnectednessScalarImageFilter was designed to work on any =
dimension data. We have been using it
for both 2D and 3D, and it works fine as long as the right parameters =
are chosen.
The minimum set of parameters you need to run =
SimpleFuzzyConnectednessScalarImageFilter includes:
(1) a seed point that is inside the object of interest. =
SetObjectSeed();
(2) the estimation of the mean and variance of the object. SetMean, =
SetVariance.
(3) a threshold value to generate the binary segmented object. (between =
0 and 1). SetThreshold.
you don't need the exact value of mean/variance, but they should be =
close to the target object, otherwise you are expecting a black volume.
also, the threshold is very important.
There are some other parameters you could use to improve the =
segmentation and was also implemented in ITK, you need to read the =
reference of Fuzzy Connectedness segmentation which was listed inside =
the .h file.
bad choice of (2) (3) can easily cause an black volume image for the =
segmentation result.
you can use=20
filter->GetFuzzyScene();
to get a ITK::Image object (in the case of 3D), which is the =
fuzzy scene. (the voxel value was scale to [0,65535]).
and then you can apply threshold using your own code or other ITK class. =
This avoids repeated computations if you got unsatifactory result just =
because the bad threshold value.
The running time varies a lot depending on how accurate is your =
estimation of the mean/variance, also the size of the volume and the =
size of the target object, and the noise level of the image data, etc...
it could take a very long time if you are dealling with high-res volume =
data. and infinite loops are unlikely to happen.
Yinpeng.
----- Original Message -----=20
From: Zein Salah=20
To: ITK Users=20
Sent: Friday, July 26, 2002 10:11 AM
Subject: [Insight-users] Fw: simple example of using any segmentation =
filter
Hi all,
=20
The SimpleFuzzyConnectednessScalarImageFilter works for a long time =
and produces just a black volume image, i.e. nothing at all can be seen.
has anybody an idea where is the problem
=20
thanks,
Zein
=20
----- Original Message -----=20
From: Zein Salah=20
To: ITK Users=20
Sent: Friday, July 26, 2002 2:48 PM
Subject: Fw: simple example of using any segmentation filter=20
=20
Hello ITK users,
=20
I have build a segmentation program that uses the=20
ConnectedThresholdImageFilter
on raw images that are read using MetaImageIO... and it worked.=20
=20
I tried to apply the same method with the=20
IsolatedConnectedImageFilter as well as with the =
SimpleFuzzyConnectednessScalarImageFilter
=20
the program went in an infinite loop.=20
=20
I realy do not know waht should the problem be.=20
1. Do not these filters work with volume data????
2. if they do, what are the parameters to be set?? to what values??
=20
=20
Thanks in advance for any kind of help.
=20
zein
=20
=20
=20
=
->8<------------->8<------------->8<------------->8<------------->8<-----=
-------->8<-
Zein I. Salah=20
Universit=E4t T=FCbingen, WSI-GRIS=20
Sand 14=20
72076 T=FCbingen=20
Email: salah@gris.uni-tuebingen.de / zeinsalah@hotmail.com
Tel.: (07071) 29 75465 (GRIS) , (07071) 96 44 39 (privat)=20
------=_NextPart_000_0026_01C2348F.9ABE5DD0
Content-Type: text/html;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
SimpleFuzzyConnectednessScalarImageFilter was =
designed to=20
work on any dimension data. We have been using it
for both 2D and 3D, and it works fine as long as the =
right=20
parameters are chosen.
The minimum set of parameters you need =
to run SimpleFuzzyConnectednessScalarImageFilter=20
includes:
(1) a seed point that is inside the =
object of=20
interest. SetObjectSeed();
(2) the estimation of the mean and =
variance of the=20
object. SetMean, SetVariance.
(3) a threshold value to generate the =
binary=20
segmented object. (between 0 and 1). SetThreshold.
you don't need the exact value of =
mean/variance,=20
but they should be close to the target object, otherwise you are =
expecting a=20
black volume.
also, the threshold is very =
important.
There are some other parameters you =
could use to=20
improve the segmentation and was also implemented in ITK, you need to =
read the=20
reference of Fuzzy Connectedness segmentation which was listed inside =
the .h=20
file.
bad choice of (2) (3) can easily cause =
an black=20
volume image for the segmentation result.
you can use
filter->GetFuzzyScene();
to get a ITK::Image<ushort,3> =
object (in the=20
case of 3D), which is the fuzzy scene. (the voxel value was scale to=20
[0,65535]).
and then you can apply threshold using =
your own=20
code or other ITK class. This avoids repeated computations if you got=20
unsatifactory result just because the bad threshold value.
The running time varies a lot depending =
on how=20
accurate is your estimation of the mean/variance, also the size of the =
volume=20
and the size of the target object, and the noise level of the image =
data,=20
etc...
it could take a very long time if you =
are dealling=20
with high-res volume data. and infinite loops are unlikely to=20
happen.
Yinpeng.
----- Original Message -----
From:=20
Zein Salah