A probability-based spectroscopic diagnostic algorithm for simultaneous discrimination of brain tumor and tumor margins from normal brain tissue

Applied Spectroscopy

Volumn 61, Issue 5, 2007, Pages 548-557

  Majumder, Shovan K ^a   Gebhart, Steven ^a   Johnson, Mahlon D ^b   Thompson, Reid ^c   Lin, Wei Chiang ^d   Mahadevan Jansen, Anita ^a  

^a VANDERBILT UNIVERSITY   (United States)

^b UNIVERSITY OF ROCHESTER SCHOOL OF MEDICINE AND DENTISTRY   (United States)

^c VANDERBILT UNIVERSITY   (United States)

^d The Department of Electrical and Computer Engineering   (United States)

Author keywords

Autofluorescence; Brain tumor; Diagnostic algorithm; Diffuse reflectance; Maximum representation and discrimination feature; MRDF; Multi class classification; Optical spectroscopy; Posterior probability; Sparse multinomial logistic regression; Tumor margin

Indexed keywords

AUTOFLUORESCENCE; BINARY CLASSIFICATION; DIAGNOSTIC ALGORITHM; DIFFUSE REFLECTANCE; POSTERIOR PROBABILITY; SPARSE MULTINOMIAL LOGISTIC REGRESSION (SMLR); TUMOR MARGIN;

ALGORITHMS; BRAIN; DIAGNOSIS; EMISSION SPECTROSCOPY; FEATURE EXTRACTION; PROBABILISTIC LOGICS;

TUMORS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN LEVEL; BRAIN TUMOR; CHEMISTRY; COMPUTER ASSISTED DIAGNOSIS; DISCRIMINANT ANALYSIS; EVALUATION; HUMAN; METHODOLOGY; SPECTROFLUOROMETRY; STATISTICAL ANALYSIS;

ALGORITHMS; BRAIN CHEMISTRY; BRAIN NEOPLASMS; DATA INTERPRETATION, STATISTICAL; DIAGNOSIS, COMPUTER-ASSISTED; DISCRIMINANT ANALYSIS; HUMANS; PATTERN RECOGNITION, AUTOMATED; SPECTROMETRY, FLUORESCENCE;

EID: 34248675227     PISSN: 00037028     EISSN: None     Source Type: Journal    
DOI: 10.1366/000370207780807704     Document Type: Article

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