简介：胎儿的ECG抽取为胎儿的监视有重要意义。这份报纸介绍基于适应线性神经网络提取胎儿的ECG的一个方法。方法能被认识到bytraining数据的小数量。另外，更好的结果能被改进神经网络结构完成。因此，更容易鉴别胎儿的ECG能被提取。试验性的结果证明适应线性神经网络能被用来有效地从母亲的腹的信号提取胎儿的ECG。而且，更清楚的胎儿的ECG能被改进神经网络结构提取。

简介：Pulmonaryvesselsextractionisachallengingtaskinclinicalmedicine.Manypulmonarydiseasesareaccompaniedbythechangesofvesseldiameters.Thevesselsandtheirbranches,whichexhibitmuchvariability,aremostimportantinperformingdiagnosisandplanningthefollow-uptherapies.Inthispaper,weproposeanefficientapproachtopulmonaryvesselsextractionbasedonthecurveevolution.Thisapproachmodelsthevesselsasmonotonicallymarchingfrontunderthespeedfieldintegratingboththeregionandtheedgeinformationwhereanewregionspeedfunctionisdesignedandintegratedwiththeedgebasedspeedfunction.Duetotheregionbasedspeedterm,thefrontcouldevenpropagateinsmallnarrowvesselbranches.Tofurtherimprovethesegmentationresults,amulti-initialfastmarchingalgorithmisdevelopedtofastimplementthenumericalsolution,whichmayavoidthemonotonicallymarchingfrontleakingoutoftheweakboundarytooearlierandalsoreducethecomputationalcost.ThevalidityofourapproachisdemonstratedbyCTpulmonaryvesselsextraction.Experimentsshowthatthesegmentationresultsbyourapproach,especiallyonthenarrowthinvesselbranchesextraction,aremoreprecisethanthatoftheexistingmethod.

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简介：Inthispaper,weproposeanovelautomaticobjectextractionalgorithm,namedtheTemplateGuidedLiveWire,basedonthepopularlyusedlivewiretechniques.Wediscussindetailsthenovelmethod'sapplicationsontongueextractionindigitalimages.Withtheguidesofagiventemplatecurvewhichapproximatesthetongue'sshape,ourmethodcanfinishtheextractionoftonguewithoutanyhumanintervention.Inthepaper,wealsodiscussedindetailshowthetemplateguidesthelivewire,andwhyourmethodfunctionsmoreeffectivelythanotherboundarybasedsegmentationmethodsespeciallythesnakealgorithm.Experimentalresultsonsometongueimagesareaswellprovidedtoshowourmethod'sbetteraccuracyandrobustnessthanthesnakealgorithm.