<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Hi Zhimin,<div> if you just need to compute the hessian and eigenvectors at a particular scale, you are better off using the HessianRecursiveGaussianImageFilter and manipulate the hessian to get the eigenvectors directly, pretty much in the same way as done in the ThreadedGenerateData method, in Code/Review/itkHessianToObjectnessMeasureImageFilter.txx</div><div><br></div><div>If, on the other hand, you need to perform a multi-scale analysis and then look at the eigenvectors, then using MultiScaleHessianBasedMeasureImageFilter is correct. In that case, the GetHessianOutput method will get you an image where each voxel holds the Hessian at the scale that gave the highest response (in terms of the generic Hessian-based measure you plug in the filter, for instance Sato's vesselness).</div><div><br></div><div>As for accessing the individual values of the Hessian, use the H(0,0), H(1,0), etc signature (see Code/Common/itkSymmetricSecondRankTensor.h). That way you can access all 9 components (except that only 6 will be stored, but that's transparent to you).</div><div><br></div><div>Hope this helps</div><div><br></div><div>Luca</div><div><br></div><div><br><div><div>On Feb 25, 2011, at 9:21 AM, Wang Zhimin wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Dear all,</span></font><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">I am a newbie to ITK. </span></font><span class="Apple-style-span" style="font-family: 'Andale Mono'; font-size: 14px; ">I currently want to compute the hessian matrix, eigen vector out of some volume CT images. I found that I can use itk::MultiScaleHessianBasedMeasureImageFilter, or itk::HessianRecursiveGaussianImageFilter plus itk::SymmetricEigenAnalysis and SymmetricSecondRankTensor image iterator to finish the job. Am I right?</span></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">For the itk::MultiScaleHessianBasedMeasureImageFilter, I understand that I can turn the GenerateHessianOutputOn() function to compute the Hessian image and use GetHessianOutput() to get the SymmetricSecondRankTensor image. Is this a correct procedure? If yes, so here comes my question. Since the multi scale hessian filter is multi scale, if I use GetHessianOutput() function, what scale is the Hessian output of?</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Suppose my volume image dimension is 3, how can I access all the values in Hessian matrix? Can I use H[][] to access all 9 values? Or I can only access 6 and I need to fill up all the rest based on symmetric rule?</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">For my second option, from HessianRecursiveGaussianImageFilter -> SymmetricSecondRankTensor image -> SymmetricEigenAnalysis -> eigen vector, will it work as predicted? </span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Sorry for so many questions. </span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Thank you and best regards,</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Zhimin</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Research Fellow</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">Institute for Infocomm Research</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;">A-STAR, Singapore</span></font></div><div><font class="Apple-style-span" face="'Andale Mono'" size="4"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></div><div><span class="Apple-style-span" style="font-family: Menlo; font-size: 11px; "><br></span></div>
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