Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing tumor confounders and molecular subtypes on MRI

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8675 LNCS, Issue PART 3, 2014, Pages 73-80

  Prasanna, Prateek ^a   Tiwari, Pallavi ^a   Madabhushi, Anant ^a  

^a Case Western Reserve University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANISOTROPY; BRAIN; DISEASES; PATHOLOGY; PIXELS; TENSORS; TEXTURES;

BIOLOGICALLY INSPIRED; CLASSIFICATION PERFORMANCE; CO-OCCURRENCE PATTERN; DISEASE PHENOTYPES; FEATURE DESCRIPTORS; GRADIENT ORIENTATIONS; HISTOGRAM OF GRADIENTS; LOCAL BINARY PATTERNS;

TUMORS;

TUMOR MARKER;

ALGORITHM; ANISOTROPY; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN TUMOR; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; DIFFERENTIAL DIAGNOSIS; HUMAN; METABOLISM; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ANISOTROPY; BRAIN NEOPLASMS; BREAST NEOPLASMS; DIAGNOSIS, DIFFERENTIAL; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TUMOR MARKERS, BIOLOGICAL;

EID: 84906969160     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10443-0_10     Document Type: Conference Paper

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