Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7623, Issue PART 1, 2010, Pages

  Ballangan, Cherry ^a   Wang, Xiuying ^a   Eberl, Stefan ^a,b   Fulham, Michael ^a,b,c   Feng, Dagan ^a,d  

^a UNIVERSITY OF SYDNEY   (Australia)

^b ROYAL PRINCE ALFRED HOSPITAL   (Australia)

^c University of Sydney   (Australia)

^d HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

NSCLC; positron emission tomography; tumor delineation; Tumor segmentation

Indexed keywords

COMMON PROBLEMS; DECISION TREE ANALYSIS; DECREASING FUNCTIONS; FALSE NEGATIVES; FALSE POSITIVE; GRADIENT MAGNITUDE; HOT SPOT; HOTSPOTS; K-MEANS CLUSTERING; LUNG TUMOR; MONOTONICITY; NSCLC; PET IMAGES; REGION EXTRACTION; REGION GROWING; SIZE AND SHAPE; TUMOR BOUNDARY; TUMOR DELINEATION; TUMOR SEGMENTATION; WHOLE BODY;

AUTOMATION; BIOLOGICAL ORGANS; DECISION TREES; FEATURE EXTRACTION; IMAGE SEGMENTATION; IMAGING SYSTEMS; MEDICAL IMAGING; POSITRON EMISSION TOMOGRAPHY; POSITRONS; THREE DIMENSIONAL;

TUMORS;

EID: 79751502808     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.844032     Document Type: Conference Paper

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