DETECTION OF SPINAL CORD INJURY USING SUPPORT VECTOR MACHINE.
Spinalcordinjuriesidentificationisthebigprobleminmagneticresonanceimaging, that use feature sets to locate the affected part of spinal cord regions. Due tochanges in shape, scale, and white matter, spontaneous detection of spinal cord atrophy iscomplicated. The important aspect that affect the diagn...
| Publicado en: | Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 2096 - 2102 |
|---|---|
| Autores principales: | , , , |
| Formato: | diagnostic images pictorial tables/charts Journal Article |
| Publicado: |
Turkish Journal of Physiotherapy & Rehabilitation
2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151006203&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151006203 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13008757 YU1 jtl: Turkish Journal of Physiotherapy Rehabilitation issn: 13008757 maglogo: N pubinfo: dt: 2021 vid: 32 iid: 2 pid: 20392 pub: Turkish Journal of Physiotherapy & Rehabilitation place: Kizilay/ Ankara, <Blank> artinfo: ui: 151006203 151006203 151006203 151006203 ppf: 2096 ppct: 6 formats: fmt: @attributes: type: P tig: atl: DETECTION OF SPINAL CORD INJURY USING SUPPORT VECTOR MACHINE. aug: au: SIVARANJANI, S. KAMALI, K. SUJINI, K. SWATHI, D. affil: Assistant Professor, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, India sug: subj: Spinal Cord Injuries Diagnosis Support Vector Machine Magnetic Resonance Imaging Gray Matter White Matter Quadriplegia Paraplegia ab: Spinalcordinjuriesidentificationisthebigprobleminmagneticresonanceimaging, that use feature sets to locate the affected part of spinal cord regions. Due tochanges in shape, scale, and white matter, spontaneous detection of spinal cord atrophy iscomplicated. The important aspect that affect the diagnosis of spinal cord injury and itsseriousness are the delineation of gray matter and white matter. Exact models for identifyingthe magnitude of spinal cord injury are classified and segmented automatically. To identifythespinalcordinjurysegments, portioningsegmentation, graphicalrepresentation, andhierarchicalsegment ationmethodsareused. Such methods also result in false positive rate in the segmented zonesandcharacteristicsdue toover-segmentation. In addition, thesetechniques of classification fails to detect the severity because of over segmentation in theaffected area. To obtain the seriousness of the injury in the over segmented area, a novelsegmentationrelatedclassificationmethodisneeded. Therecommendednon-linearthresholdbasedsupportvectormachineiseffectiveforSCIdetectionamongtheseconventional feature segmentation based classification models. Thus, the output have to showthatthecurrent model is moreaccuratethan previousmodels. pubtype: Academic Journal doctype: diagnostic images pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|