Classification of lung nodules using CT images based on texture features and fractal dimension transformation

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A new computer-aided detection (CAD) system for lung nodule detection and selection in computed tomography scans is substantiated and implemented. The method consists of the following stages: preprocessing based on threshold and morphological filtration, the formation of suspicious regions of interest using a priori information, the detection of lung nodules by applying the fractal dimension transformation, the computation of informative texture features for identified lung nodules, and their classification by applying the SVM and AdaBoost algorithms. A physical interpretation of the proposed CAD system is given, and its block diagram is constructed. The simulation results based on the proposed CAD method demonstrate advantages of the new approach in terms of standard criteria, such as sensitivity and the false-positive rate.

About the authors

V. F. Kravchenko

Kotelnikov Institute of Radio Engineering and Electronics of the Russian Academy of Sciences; Scientific and Technological Centre of Unique Instrumentation of the Russian Academy of Sciences; Bauman Moscow State Technical University

Author for correspondence.

Russian Federation, 11-7, Mokhovaya street, Moscow, 125009; 15, Bytlerova street, Moscow, 117342; 5, 2-nd Baumanskaya, Moscow, 105005

V. I. Ponomaryov

Instituto Politecnico Nacional


Mexico, 102, Macayo, Villahermosa, 86020

V. I. Pustovoit

Scientific and Technological Centre of Unique Instrumentation of the Russian Academy of Sciences


Russian Federation, 15, Bytlerova street, Moscow, 117342

Academician of the Russian Academy of Sciences

E. Rendon-Gonzalez

Instituto Politecnico Nacional


Mexico, 102, Macayo, Villahermosa, 86020


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