An automated segmentation approach for highlighting the histological complexity of human lung cancer

Annals of Biomedical Engineering

Volumn 38, Issue 12, 2010, Pages 3581-3591

  Sieren, J C ^a,b,c   Weydert, J ^b   Bell, A ^b   De Young, B ^b   Smith, A R ^a,b   Thiesse, J ^a   Namati, E ^a   McLennan, Geoffrey ^a,b,c  

^a UNIVERSITY OF IOWA   (United States)

^b UNIVERSITY OF IOWA   (United States)

^c IA United States   (United States)

Author keywords

Adenocarcinoma; Computer analysis; Histology; Immunohistochemistry; Lung nodule; Pathology; Quantification

Indexed keywords

ADENOCARCINOMA; COMPUTER ANALYSIS; IMMUNOHISTOCHEMISTRY; LUNG NODULE; QUANTIFICATION;

AUTOMATION; DISEASES; HISTOLOGY; PATHOLOGY; TISSUE;

BIOLOGICAL ORGANS;

ALGORITHM; ARTICLE; BIOMEDICAL ENGINEERING; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE PROCESSING; IMMUNOHISTOCHEMISTRY; LUNG TUMOR; METHODOLOGY; PATHOLOGY; STAINING;

ALGORITHMS; BIOMEDICAL ENGINEERING; DIAGNOSIS, COMPUTER-ASSISTED; HISTOLOGICAL TECHNIQUES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMMUNOHISTOCHEMISTRY; LUNG NEOPLASMS; STAINING AND LABELING;

EID: 78651399309     PISSN: 00906964     EISSN: 15739686     Source Type: Journal    
DOI: 10.1007/s10439-010-0103-6     Document Type: Article

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