A framework for automated tumor detection in thoracic FDG PET images using texture-based features

Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Volumn , Issue , 2009, Pages 97-100

  Saradhi, G V ^a   Gopalakrishnan, G ^a   Roy, A S ^a   Mullick, R ^a   Manjeshwar, R ^b   Thielemans, K ^c   Patil, U ^d  

^a GE GLOBAL RESEARCH   (India)

^b GE GLOBAL RESEARCH   (United States)

^c Hammersmith Imanet   (United Kingdom)

^d MANIPAL HOSPITAL   (India)

Author keywords

Gray level co occurrence matrix; Logit boost; Positron emission tomography (PET); Texture; Tumor classification

Indexed keywords

CONNECTED COMPONENT ANALYSIS; CROSS VALIDATION; DATA SETS; FALSE POSITIVE; FALSE POSITIVE RATES; FDG PET; FEATURE VECTORS; GRAY-LEVEL CO-OCCURRENCE MATRIX; LOGIT BOOST; PET IMAGES; SECOND ORDERS; TEST DATA; TEXTURE FEATURES; THRESHOLDING; TRUE POSITIVE RATES; TUMOR CLASSIFICATION; TUMOR DETECTION; UPTAKE VALUES; VOLUME OF INTEREST;

CLASSIFIERS; IMAGE REGISTRATION; LEARNING SYSTEMS; MATRIX ALGEBRA; POSITRONS; STATISTICAL TESTS; TEXTURES; TUMORS;

POSITRON EMISSION TOMOGRAPHY;

EID: 70449371583     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2009.5192992     Document Type: Conference Paper

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