A NOVEL MRI IMAGE RECONSTRUCTION USING COMPRESSED SENSING AND ITS CLASSIFICATION USING SUPPORT VECTOR MACHINE

Magnetic iresonance iimaging i(MRI)iis ian iimaging itechnique ithat ihas iplayed ian iimportant irole iin ineuroscience iresearch ifor istudying ibrain iimages i.X-ray iis ilikewise iexceptionally ihelpful ifor ianalyzing ithe icerebrum iand ispinal irope irelated iissues. iThe isize iof ithe ipicture ichooses ihow ioften ithe iRadio iFrequency ibeat ishould ibe iapplied, isubsequently imaking ithe iMRI iexamine ia itedious iprocedure. iThere iis ia ideveloping iprerequisite ifor idecreasing ithe idiagnosing itime iin iMRI irequiring iexamination ito iquicken ithis inon idirect istreamlining iissue. iCompressed iSensing i(CS) iaims ito ireconstruct iimages ifrom iconsiderably ismaller imeasurements ithan iwere ithought ibefore. iApplying iCS ito iMRI ioffers ipotentially isignificant iscan itime ireductions. iA itechnique ito iMRI iremaking ifrom iunder iexamined iestimations iis iproposed iin ithis ipaper. iDiscrete iWavelet iTransform iis iutilized ito imeagerly iportray iMRI. iCS iremaking iis iperformed iutilizing il1 istandard iby iapplying iBasis ipursuit iprimal- idual iinterior ipoint imethod. iTrial iresults iuncover ithat ithe iproposed istrategy irecreates ipictures iwith igreat iquality. iClassification iis ian iimportant ipart iin iretrieval isystem iin iorder ito idistinguish ibetween inormal ipatients iand ithose iwho ihave ithe ipossibility iof ihaving iabnormalities ior itumor. iIn ithis ipaper, iwe ihave iobtained ithe ifeature irelated ito iMRI iimages iusing idiscrete iwavelet itransformation. iAn iadvanced ikernel ibased itechniques isuch ias iSupport iVector iMachine i(SVM) ifor ithe iclassification iof ivolume iof iMRI idata ias inormal iand iabnormal iwill ibe ideployed.