Re: [Gdcm2] Automatically categorizing and polygonizing scanned tissue
Cross-platform DICOM implementation
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From: John D. <jdx...@go...> - 2011-10-03 14:16:42
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Is it the polygonization, or the tissue/organ categorization, which is the big problem? My guess is the latter? On 3 October 2011 14:34, Mark Roden <mm...@gm...> wrote: > This is _extremely_ hard to do, and worthy of a couple of doctoral > dissertations. > > Take a look at the MICCAI segmentation challenges (Just google for > 'MICCAI grand segmentation challenge') to see the state of the art in > segmenting various organs from various modalities. > > > On Mon, Oct 3, 2011 at 6:30 AM, John Dexter <jdx...@go...> > wrote: > > If I receive say a CT/MRI patient scan, how easy is it to automatically > > identify which is the heart, skeleton, etc? And how easy is it to > > automatically build polygonal representations from volume data? The > latter > > part I think one of the other toolkits might solve, but could you ever > trust > > a completely automated solution or would it always involve manual > > review/optimization? > > > ------------------------------------------------------------------------------ > > All the data continuously generated in your IT infrastructure contains a > > definitive record of customers, application performance, security > > threats, fraudulent activity and more. Splunk takes this data and makes > > sense of it. Business sense. IT sense. Common sense. > > http://p.sf.net/sfu/splunk-d2dcopy1 > > _______________________________________________ > > Gdcm-developers mailing list > > Gdc...@li... > > https://lists.sourceforge.net/lists/listinfo/gdcm-developers > > > > > |