Characterization of lung nodule malignancy using hybrid shape and appearance features

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

Volumn 9900 LNCS, Issue , 2016, Pages 662-670

  Buty, Mario ^a   Xu, Ziyue ^a   Gao, Mingchen ^a   Bagci, Ulas ^b   Wu, Aaron ^a   Mollura, Daniel J ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Conformal mapping; Deep convolutional neural network; Nodule characterization; Random forest; Spherical harmonics

Indexed keywords

BIOLOGICAL ORGANS; COMPUTERIZED TOMOGRAPHY; CONFORMAL MAPPING; CONVOLUTION; CONVOLUTIONAL NEURAL NETWORKS; DECISION TREES; DEEP NEURAL NETWORKS; DIAGNOSIS; DISEASES; HARMONIC ANALYSIS; MEDICAL COMPUTING; RANDOM FORESTS;

CLINICAL PRACTICES; COMPUTER AIDED DIAGNOSTICS; HIGH-ACCURACY; IMAGE DATABASE; LUNG CANCER DIAGNOSIS; RANDOM FOREST CLASSIFIER; SETS OF FEATURES; SPHERICAL HARMONICS;

MEDICAL IMAGING;

EID: 84996503636     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46720-7_77     Document Type: Conference Paper

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