A new 2.5D representation for lymph node detection using random sets of deep convolutional neural network observations

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8673 LNCS, Issue PART 1, 2014, Pages 520-527

  Roth, Holger R ^a   Lu, Le ^a   Seff, Ari ^a   Cherry, Kevin M ^a   Hoffman, Joanne ^a   Wang, Shijun ^a   Liu, Jiamin ^a   Turkbey, Evrim ^a   Summers, Ronald M ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BODY FLUIDS; NEURAL NETWORKS; CONVOLUTION; DIAGNOSIS; MEDICAL COMPUTING; MEDICAL IMAGING;

3-D HAAR FEATURES; CANDIDATE GENERATION; CENTROID COORDINATES; CLINICAL DIAGNOSTICS; CONVOLUTIONAL NEURAL NETWORK; HARVEST VOLUMES; LYMPH NODE DETECTIONS; ORTHOGONAL VIEWS;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE QUALITY; LYMPH NODE; LYMPHATIC SYSTEM DISEASE; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGING, THREE-DIMENSIONAL; LYMPH NODES; LYMPHATIC DISEASES; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84909644435     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10404-1_65     Document Type: Conference Paper

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