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Volumn 341, Issue 1, 2012, Pages

Predicting Alzheimer's disease by classifying 3D-Brain MRI images using SVM and other well-defined classifiers

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; DATABASE SYSTEMS; DIAGNOSIS; IMAGE CLASSIFICATION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; NEUROIMAGING; PATTERN RECOGNITION; POPULATION STATISTICS;

EID: 84858392734     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/341/1/012019     Document Type: Conference Paper
Times cited : (6)

References (21)
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  • 8
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    • Horowitz, S and Pavlidis, T 1977 Picture segmentation by a directed split and merge procedure CMetImAly 77 101-111
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    • Horowitz, S.1    Pavlidis, T.2
  • 9
    • 0024700097 scopus 로고
    • A theory for multi-resolution signal decomposition: The wavelet representation. IEEE Trans
    • Mallat, S G 1989 A theory for multi-resolution signal decomposition: The wavelet representation. IEEE Trans Pattern Anal. Mach. Intell. 11 674-693
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    • Mallat, S.G.1
  • 13
    • 0018306059 scopus 로고
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    • Otsu, N.1
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    • Taylor, C.1
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    • Comparative assessment of statistical brain MR image segmentation algorithms and their impact on partial volume correction in PET
    • DOI 10.1016/j.neuroimage.2006.05.031, PII S1053811906005799
    • Zaidi H, Ruest T, Schoenahl F, Montandon ML 2006 Comparative assessment of statistical brain MR image segmentation algorithms and their impact on partial volume correction in PET Neuroimage. 32 1591-1607 (Pubitemid 44332287)
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  • 21
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    • Support-vector network
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.