<div>hello luis,</div> <div>thank you for your suggestation.I took a look at Iterativeclosestpoint 2 and it seems ok to me,but how can I Segment the fiducial from my preoperative MRI image.<BR>and Generate with them a list of point coordinates (x,y,z)?</div> <div>the second question is that:when I do the task above,shall I make a txt file(like IterativeClosestPointFixedPoints) containing the the point coordinate ?</div> <div>thanks alot for your help</div> <div>Alireza<BR><BR><B><I>Luis Ibanez <luis.ibanez@kitware.com></I></B> wrote:</div> <BLOCKQUOTE class=replbq style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #1010ff 2px solid"><BR><BR>Hi Alireza,<BR><BR><BR>You are dealing with at 2D / 3D registration problem.<BR><BR><BR>Here is one possible way to address it:<BR><BR><BR>1) Segment the fiducial from your preoperative MRI image.<BR>Generate with them a list of point coordinates (x,y,z).<BR>Load those coordinates into an
itkPointSet.<BR><BR>2) Segment the black&white patters from the 2D video image<BR>Load those coordinates into an itkPointSet.<BR><BR>3) Use the itkRigid3DPerspectiveTransform.h along with the<BR>PointSetToPointSetRegistration framework that is described<BR>in the Examples:<BR><BR>Insight/Examples/Patented/<BR>IterativeClosestPoint1.cxx<BR>IterativeClosestPoint2.cxx<BR>IterativeClosestPoint3.cxx<BR><BR><BR><BR>Regards,<BR><BR><BR>Luis<BR><BR><BR>---------------------<BR>Alireza Salamy wrote:<BR>> *Hi all Insight users,*<BR>> *I am working on the project which is displaying of MR images in the <BR>> operation room by means of Mixed reality for future use in neurosurgical <BR>> operation rooms.this involves fusion of optical images from a web camera <BR>> with preoperatively acquired MRI images.the geometrical correspondence <BR>> between optical and MRI images is to be carried out in two <BR>> steps:1-initial registration of MRI and physical
reality.2-real-time <BR>> tracking to compensate for motion of the camera relative to the MRI <BR>> image.my duty deals with the first problem.*<BR>> *I construct a phantom that is visible both in MRI images and optical <BR>> images.this is used together with a bitting fixation device to achieve a <BR>> reproducible position relative to the skull.It contain at least 3 points <BR>> identifiable in MRI images,e.g.containing a lipid with characteristic <BR>> MRI signal,as well as a structure easily recognized in the optical <BR>> image,e.g a simple geometrical pattern in Black and White.*<BR>> *It would be great if you recommend me an algorithm for registration <BR>> between the phantom that I made and physical reality,finding the <BR>> geometrical relationship(transformation matrix) between the volunteer 's <BR>> head and the phantom.this involves identifying the MRI-visible points in <BR>> the phantom and using the known geometric
relationship between these and <BR>> the optical pattern.*<BR>> *thank you very much for your help.*<BR>> *Alireza*<BR>> ** <BR>> <BR>> <BR>> <BR>> <BR>> <BR>> <BR>> <BR>> ------------------------------------------------------------------------<BR>> Food fight? <BR>> <HTTP: index;_ylc="X3oDMTFvbGNhMGE3BF9TAzM5NjU0NTEwOARfcwMzOTY1NDUxMDMEc2VjA21haWxfdGFnbGluZQRzbGsDbWFpbF90YWcx?link=ask&sid=396545367" answers.yahoo.com><BR>> Enjoy some healthy debate<BR>> in the Yahoo! Answers Food & Drink Q&A. <BR>> <HTTP: index;_ylc="X3oDMTFvbGNhMGE3BF9TAzM5NjU0NTEwOARfcwMzOTY1NDUxMDMEc2VjA21haWxfdGFnbGluZQRzbGsDbWFpbF90YWcx?link=ask&sid=396545367" answers.yahoo.com><BR>> <BR>> <BR>> <BR>> ------------------------------------------------------------------------<BR>> <BR>> _______________________________________________<BR>> Insight-users mailing list<BR>> Insight-users@itk.org<BR>>
http://www.itk.org/mailman/listinfo/insight-users<BR></BLOCKQUOTE><BR><p> 
<hr size=1>Don't pick lemons.<br>
See all the <a href="http://autos.yahoo.com/new_cars.html;_ylc=X3oDMTE0OGRsc3F2BF9TAzk3MTA3MDc2BHNlYwNtYWlsdGFncwRzbGsDbmV3Y2Fycw--">new 2007 cars</a> at <a href="http://autos.yahoo.com/new_cars.html;_ylc=X3oDMTE0OGRsc3F2BF9TAzk3MTA3MDc2BHNlYwNtYWlsdGFncwRzbGsDbmV3Y2Fycw--">Yahoo! Autos.</a>