Clustering methods applied in the detection of Ki67 hot-spots in whole tumor slide images: An efficient way to characterize heterogeneous tissue-based biomarkers

Cytometry Part A

Volumn 81 A, Issue 9, 2012, Pages 765-775

  Lopez, Xavier Moles ^a,b   Debeir, Olivier ^a   Maris, Calliope ^c   Rorive, Sandrine ^c   Roland, Isabelle ^c   Saerens, Marco ^d   Salmon, Isabelle ^b,c   Decaestecker, Christine ^a,b  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

^b Center for Microscopy and Molecular Imaging (CMMI)   (Belgium)

^c ERASME HOSPITAL   (Belgium)

^d UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

Biomarker; Cell proliferation; Clustering; Image processing; Immunohistochemistry; Tissue slide digitization

Indexed keywords

KI 67 ANTIGEN; TUMOR MARKER;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; COMPUTER SIMULATION; GLIOMA; HUMAN; METABOLISM; PATHOLOGY;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTER SIMULATION; GLIOMA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; KI-67 ANTIGEN; MODELS, BIOLOGICAL; SOFTWARE; TUMOR MARKERS, BIOLOGICAL;

EID: 84865417552     PISSN: 15524922     EISSN: 15524930     Source Type: Journal    
DOI: 10.1002/cyto.a.22085     Document Type: Article

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