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Volumn 1, Issue , 2003, Pages 614-617

Optimal Feature Combination for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED DESIGN; FEATURE EXTRACTION; IMAGE SEGMENTATION; PROBLEM SOLVING; RADIOLOGY; SENSITIVITY ANALYSIS; STATISTICAL METHODS; TUMORS; ULTRASONICS;

EID: 1542362428     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (12)
  • 1
    • 0027433810 scopus 로고
    • Current role of MR imaging in staging of Adenocarcinoma of the prostate
    • M. Schiebler, M. Schnall et al., "Current role of MR imaging in staging of Adenocarcinoma of the prostate", Acad. Radiol., 1993, vol. 189(2), pp. 339-52.
    • (1993) Acad. Radiol. , vol.189 , Issue.2 , pp. 339-352
    • Schiebler, M.1    Schnall, M.2
  • 3
    • 0027750778 scopus 로고
    • Texture Analysis of Ultrasonic Images of the Prostate by Means of Co-occurrence Matrices
    • D. Basset, Z. Sun, et al., "Texture Analysis of Ultrasonic Images of the Prostate by Means of Co-occurrence Matrices", Ultrasonic Imaging, 1993, vol. 15, pp. 218-237.
    • (1993) Ultrasonic Imaging , vol.15 , pp. 218-237
    • Basset, D.1    Sun, Z.2
  • 5
    • 1542287867 scopus 로고    scopus 로고
    • Interplay of Intensity Standardization and Inhomogeneity Correction in MRI Analysis
    • To Appear
    • A. Madabhushi, J. Udupa, "Interplay of Intensity Standardization and Inhomogeneity Correction in MRI Analysis", To Appear in SPIE, 2003.
    • (2003) SPIE
    • Madabhushi, A.1    Udupa, J.2
  • 7
    • 0026398342 scopus 로고
    • Unsupervised Texture Segmentation Using Gabor Filters
    • A. Jain, F. Farrokhnia, "Unsupervised Texture Segmentation Using Gabor Filters", Pattern Recog., 1991, vol. 24[12], pp. 1167-1186.
    • (1991) Pattern Recog. , vol.24 , Issue.12 , pp. 1167-1186
    • Jain, A.1    Farrokhnia, F.2
  • 10
    • 0032645080 scopus 로고    scopus 로고
    • An Empirical Classification of Voting Classification Algorithms
    • E. Bauer, R. Kohavi, "An Empirical Classification of Voting Classification Algorithms", Machine Learning, 1999, vol. 36, pp. 105-42..
    • (1999) Machine Learning , vol.36 , pp. 105-142
    • Bauer, E.1    Kohavi, R.2
  • 11
    • 0036146454 scopus 로고    scopus 로고
    • The problem of bias in training data in regression problems in medical decision support
    • B. Mac Namee et al., "The problem of bias in training data in regression problems in medical decision support", Artif. Intel. in Med., 2002, vol. 36, pp. 51-70.
    • (2002) Artif. Intel. in Med. , vol.36 , pp. 51-70
    • Mac Namee, B.1
  • 12
    • 0041874655 scopus 로고    scopus 로고
    • Interaction between noise suppression & inhomogeneity correction
    • To Appear
    • A. Montillo, J. Udupa, L. Axel, D. Metaxas, "Interaction between noise suppression & inhomogeneity correction", To Appear in SPIE, 2003.
    • (2003) SPIE
    • Montillo, A.1    Udupa, J.2    Axel, L.3    Metaxas, D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.