A texture feature analysis for diagnosis of pulmonary nodules using LIDC-IDRI database

ICMIPE 2013 - Proceedings of 2013 IEEE International Conference on Medical Imaging Physics and Engineering

Volumn , Issue , 2013, Pages 14-18

  Han, Fangfang ^a,b   Zhang, Guopeng ^c   Wang, Huafeng ^b   Song, Bowen ^b   Lu, Hongbing ^c   Zhao, Dazhe ^a   Zhao, Hong ^a   Liang, Zhengrong ^b  

^a NORTHEASTERN UNIVERSITY   (China)

^b STONY BROOK UNIVERSITY   (United States)

^c FOURTH MILITARY MEDICAL UNIVERSITY   (China)

Author keywords

3D Haralick Texture Features; LIDC IDRI Database; Malignancy Diagnosis; Pulmonary Nodules; ROC; SVM

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DATABASE SYSTEMS; MEDICAL IMAGING; SUPPORT VECTOR MACHINES;

AREA UNDER THE CURVES; CLASSIFICATION RESULTS; HARALICK TEXTURE FEATURES; PULMONARY NODULES; RECEIVER OPERATING CHARACTERISTICS; ROC; SVM; TEXTURE ANALYSIS METHOD;

TEXTURES;

EID: 84906899970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMIPE.2013.6864494     Document Type: Conference Paper

References (13)

1. Heber MacMahon, John H. M. Austin, Gordon Gamsu, Christian J. Herold, James R. Jett, David P. Naidich, et al., Guidelines for Management of Small Pulmonary Nodules Detected on CT Scans: A Statement from the Fleischner Society, Radiology, Vol. 237, 395-400, 2005.
2. Bram van Ginneken, Bart M. ter Haar Romeny, and Max A. Viergever, Computer-Aided Diagnosis in Chest Radiography: A Survey, IEEE Transactions on Medical Imaging, Vol. 20, No. 12, 1228-1241, 2001.
3. K DOI, Current Status and Future Potential of Computer-Aided Diagnosis in Medical Imaging, The British Journal of Radiology, Vol. 78, S3-S19, 2005.
4. Ayman El-Baz, Garth M. Beache, Georgy Gimel' farb, Kenji Suzuki, Kazunori Okada, Ahmed Elnakib, et al., Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies, International Journal of Biomedical Imaging, 2013.
5. Ingrid C. Sluimer, Paul F. van Waes, Max A. Viergever, and Bram van Ginneken, Computer-Aided Diagnosis in High Resolution CT of the Lungs, Medical Physics, Vol. 30, No. 12, 3081-3090, 2003.
6. Michael K. Gould, James Fletcher, Mark D. Iannettoni, William R. Lynch, David E. Midthun, David P. Naidich, and David E. Ost, Evaluation of Patients with Pulmonary Nodules: When is It Lung Cancer? ACCP Evidence-Based Clinical Practice Guidelines, Chest, Vol. 132, 108S-130S, 2007.
7. Dmitriy Zinovev, Daniela Raicu, Jacob Furst, and Samuel G. Armato III, Predicting Radiological Panel Opinions Using a Panel of Machine Learning Classifiers, Algorithms, Vol. 2, 1473-1502, 2009.
8. Fangfang Han, Huafeng Wang, Bowen Song, Guopeng Zhang, Hongbing Lu, William Moore, Zhengrong Liang and Hong Zhao, A New 3D Texture Feature Based Computer-Aided Diagnosis Approach to Differentiate Pulmonary Nodules, Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702Z (February 28, 2013).
9. Rafael Wiemker, Martin Bergtholdt, Ekta Dharaiya, Sven Kabus and Michael C. Lee, Agreement of CAD features with expert observer ratings for characterization of pulmonary nodules in CT using the LIDC-IDRI database, Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72600H (February 27, 2009).
10. Samuel G. Armato III, Geoffrey Mclennan, Luc Bidaut, Michael F. McNitt-Gray, Charles R. Meyer, Anthony P. Reeves, et al., The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans, Medical Physics, Vol. 38, 915-931, 2011.
11. Robert M. Haralick, K. Shanmugam, and Its'Hak Dinstein, Textural Features for Image Classification, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-3, No. 6, 610-621, November 1973.
12. Frederick N. Fritsch and Robert E. Carlson, Monotone Piecewise Cubic Interpolation, Society for Industrial and Applied Mathematics, Vol. 17, No. 2, 238-246, 1980.
13. Johan Suykens, Joos Vandewalle, Least Squares Support Vector Machine Classifiers, Neural Processing Letters, Vol. 9, No. 3, 293-300, June 1999