TY - JOUR
T1 - Recognition of pulmonary nodules in thoracic CT scans using 3-D deformable object models of different classes
AU - Takizawa, Hotaka
AU - Yamamoto, Shinji
AU - Shiina, Tsuyoshi
PY - 2010/6
Y1 - 2010/6
N2 - The present paper describes a novel recognition method of pulmonary nodules (i.e., cancer candidates) in thoracic computed tomography scans by use of three-dimensional spherical and cylindrical models that represent nodules and blood vessels, respectively. The anatomical validity of these object models and their fidelity to computed tomography scans are evaluated based on the Bayes theorem. The nodule recognition is employed by the maximum a posteriori estimation. The proposed method is applied to 26 actual computed tomography scans, and experimental results are shown.
AB - The present paper describes a novel recognition method of pulmonary nodules (i.e., cancer candidates) in thoracic computed tomography scans by use of three-dimensional spherical and cylindrical models that represent nodules and blood vessels, respectively. The anatomical validity of these object models and their fidelity to computed tomography scans are evaluated based on the Bayes theorem. The nodule recognition is employed by the maximum a posteriori estimation. The proposed method is applied to 26 actual computed tomography scans, and experimental results are shown.
KW - Bayes theorem
KW - Maximum a posteriori estimation
KW - Recognition of pulmonary nodules
KW - Thoracic computed tomography scans
KW - Three-dimensional deformable object models
UR - http://www.scopus.com/inward/record.url?scp=80054865328&partnerID=8YFLogxK
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U2 - 10.3390/a3020125
DO - 10.3390/a3020125
M3 - Article
AN - SCOPUS:80054865328
VL - 3
SP - 125
EP - 144
JO - Algorithms
JF - Algorithms
SN - 1999-4893
IS - 2
ER -