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Volumn , Issue , 2005, Pages 436-441

The use of co-occurrence features in medical imaging: An empirical study

Author keywords

Computed tomography; Medical imaging; Textural analysis

Indexed keywords

CLASSIFICATION ACCURACY; CO-OCCURRENCE FEATURES; CO-OCCURRENCE-MATRIX; COMPUTED TOMOGRAPHY SCAN; EMPIRICAL STUDIES; STATISTICAL FEATURES; TEXTURAL ANALYSIS; USER-DEFINED PARAMETERS;

EID: 84887237971     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2)

References (14)
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    • Chan, H.P., Sahiner, B., Petrick, N., Helvie, M., Lam, K., Adler, D., Goodsit, M.: Computerized classification of malignant and benign microclassifications on mammograms: texture analysis using an artificial neural network. Phys. Med. Biol. 42 (1997) 549-567
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    • Chan, H.P.1    Sahiner, B.2    Petrick, N.3    Helvie, M.4    Lam, K.5    Adler, D.6    Goodsit, M.7
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    • 0041428219 scopus 로고    scopus 로고
    • Obstructive lung diseases: Texture classification for differentiation at ct
    • Chabat, F., Yang, G.S., Hansell, D.: Obstructive lung diseases: Texture classification for differentiation at ct. Radiology 228 (1999) 871-877
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    • Chabat, F.1    Yang, G.S.2    Hansell, D.3
  • 13
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    • Feature search algorithms
    • C.H.Chin, ed.: Alphen aan den Rijn, The Netherlands
    • Kittler, J.: Feature search algorithms. In C.H.Chin, ed.: Pattern Recognition and Signal Processing. Alphen aan den Rijn, The Netherlands (1998) 41-60
    • (1998) Pattern Recognition and Signal Processing , pp. 41-60
    • Kittler, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.