Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis

Journal of Thoracic Oncology

Volumn 12, Issue 3, 2017, Pages 501-509

  Luo, Xin ^a   Zang, Xiao ^a   Yang, Lin ^a,b   Huang, Junzhou ^c   Liang, Faming ^d   Rodriguez Canales, Jaime ^e   Wistuba, Ignacio I ^e   Gazdar, Adi ^f   Xie, Yang ^a   Xiao, Guanghua ^a  

^a UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^b CANCER HOSPITAL   (China)

^c UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

^d UNIVERSITY OF FLORIDA   (United States)

^e UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^f UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

Lung adenocarcinoma; Lung squamous cell carcinoma; Morphological features; Pathological image; Prognosis; Statistical modeling

Indexed keywords

EOSIN; HEMATOXYLIN;

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; CANCER PATIENT; CANCER PROGNOSIS; CANCER STAGING; COHORT ANALYSIS; CONTROLLED STUDY; FEMALE; HIGH RISK POPULATION; HISTOPATHOLOGY; HUMAN; HUMAN CELL; HUMAN TISSUE; IMAGE ANALYSIS; LOW RISK POPULATION; LUNG ADENOCARCINOMA; LUNG CANCER; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; NON SMALL CELL LUNG CANCER; OVERALL SURVIVAL; PATHOLOGICAL TISSUE; PREDICTION; QUANTITATIVE ANALYSIS; SEX DIFFERENCE; SMOKING; SQUAMOUS CELL LUNG CARCINOMA; VERY ELDERLY; ADENOCARCINOMA; DISEASE EXACERBATION; FOLLOW UP; IMAGE PROCESSING; LUNG TUMOR; PATHOLOGY; PROCEDURES; PROGNOSIS; SQUAMOUS CELL CARCINOMA; STATISTICAL MODEL; SURVIVAL RATE;

ADENOCARCINOMA; AGED; CARCINOMA, NON-SMALL-CELL LUNG; CARCINOMA, SQUAMOUS CELL; DISEASE PROGRESSION; FEMALE; FOLLOW-UP STUDIES; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LUNG NEOPLASMS; MALE; MIDDLE AGED; MODELS, STATISTICAL; NEOPLASM STAGING; PROGNOSIS; SURVIVAL RATE;

EID: 85015306784     PISSN: 15560864     EISSN: 15561380     Source Type: Journal    
DOI: 10.1016/j.jtho.2016.10.017     Document Type: Article

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