title: A comparative study for 2D and 3D computer-aided diagnosis methods for solitary pulmonary nodules.
abstract: Many computer-aided diagnosis (CAD) methods, including 2D and 3D approaches, have been proposed for solitary pulmonary nodules (SPNs). However, the detection and diagnosis of SPNs remain challenging in many clinical circumstances. One goal of this work is to investigate the relative diagnostic accuracy of 2D and 3D methods. An additional goal is to develop a two-stage approach that combines the simplicity of 2D and the accuracy of 3D methods. The experimental results show statistically significant differences between the diagnostic accuracy of 2D and 3D methods. The results also show that with a very minor drop in diagnostic performance the two-stage approach can significantly reduce the number of nodules needed to be processed by the 3D method, streamlining the computational demand.
authors.affiliation: Department of Mechanical and Electromechanical Engineering, National Sun-Yat Sen University, Kaohsiung, Taiwan, Republic of China. chinsonyeh@gmail.com
authors.forename: Chinson
authors.initials: C
authors.lastname: Yeh
authors.forename: Jen-Feng
authors.initials: JF
authors.lastname: Wang
authors.forename: Ming-Ting
authors.initials: MT
authors.lastname: Wu
authors.forename: Chen-Wen
authors.initials: CW
authors.lastname: Yen
authors.forename: Mark L
authors.initials: ML
authors.lastname: Nagurka
authors.forename: Chen-Liang
authors.initials: CL
authors.lastname: Lin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003287:Contrast Media; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D021621:Imaging, Three-Dimensional; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed
chemical_list: D003287:Contrast Media