A fully automatic extraction of magnetic resonance image features in glioblastoma patients

Medical Physics

Volumn 41, Issue 4, 2014, Pages

  Zhang, Jing ^a   Barboriak, Daniel P ^a   Hobbs, Hasan ^a   Mazurowski, MacIej A ^a  

^a DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

computer vision; glioblastoma; segmentation; tumor; VASARI feature

Indexed keywords

CELL DEATH; COMPUTER VISION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; TUMORS;

AUTOMATIC EXTRACTION; CORRELATION COEFFICIENT; GLIOBLASTOMAS; MAJOR AXIS LENGTHS; MANUAL SEGMENTATION; OPTIMIZED TREATMENT PLANNING; READER VARIABILITY; VASARI FEATURE;

DIAGNOSIS;

ACCURACY; ALGORITHM; ARTICLE; AUTOANALYSIS; BRAIN REGION; CANCER PATIENT; CANCER SURVIVAL; COMPUTER SIMULATION; CONTROLLED STUDY; CORRELATION COEFFICIENT; GLIOBLASTOMA; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSOR; INTERMETHOD COMPARISON; MAJOR CLINICAL STUDY; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTIVE VALUE; STANDARD; THICKNESS; TUMOR NECROSIS; TUMOR VOLUME; AUTOMATION; BRAIN NEOPLASMS; IMAGE PROCESSING; PROCEDURES;

ALGORITHMS; AUTOMATION; BRAIN NEOPLASMS; GLIOBLASTOMA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING;

EID: 84896133294     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.4866218     Document Type: Article

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