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http://dx.doi.org/10.5762/KAIS.2015.16.1.507

Application of Computer-Aided Diagnosis a using Texture Feature Analysis Algorithm in Breast US images  

Lee, Jin-Soo (Department of Radiology, Inje University Heaundae Paik Hospital)
Kim, Changsoo (Department of Radiological, College of Health Sciences, Catholic University of Pusan)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.16, no.1, 2015 , pp. 507-515 More about this Journal
Abstract
This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.
Keywords
Breast ultrasound images; Computer-Aided Diagnosis; TFA parameters algorithm;
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1 National Cancer Information Center, "htt://www.cancer.go.kr/mbs/cancer/subview.jspid, 2011.
2 H. J. Yoon, M. H. Kim, Y. H. Choi, "Effective Computer-Aided Diagnosis Analysis for the Plaque Measurement on the Ultrasound image of the Carotid Artery", J Korean Soc. Ultrasound in Medicine, 23, 2, pp.105-111, 2004.   과학기술학회마을
3 S. H. Choi, S. Y. Chung, W. K. Lee, I. K. Yang, H. D Kim, J. S. Shin, B. H. Jung, W. J. Shin, H. H. Kim, S. H. Kim, "Ultrasonography in Paget's Disease of Breast:Comparison with Mammographic Finding", J Korean Soc. Ultrasound in Medicine, 20, 2, pp.137-142, 2001.
4 Y. W. Sun, Y. J. Song, H. Y. Yun, D. H. Ryu, "Management fo Breast Masses Detected Only by Ultrasonography" Journal of Breast Cancer, 7, 1, pp.43-48, 2004.
5 P. H. Arger, C. M. Sehgal, E, F. Conant, J. Zukerman, S. E. Rowling, J. A. Patton. "Interreader variability and predictive value of US descriptions of solid breast masses: pilot study", Acad Radiol, 8, 4, pp.335-342, 2001.   DOI
6 E. H. Lee, J. H. Cha, B. J. Cho, Y. H. Koh, B. J. Youn, W. K. Moon "Breast Imaging Reporting and Data System9BI-RADS) US leexion and Final Assesment Category for Solid Breast Masses: the Rates of Inter-and Intraobserver Agreement" J. Korean Soc. Radiology, 56, 6, pp.593-601, 2007.   DOI
7 M. R. De Mello, D. M. Albuquerque, F. G. Pereira-Cunha, K. B. Albanez, K. B. Pagnano, F. F. Costa, K. Metze, I. Lorand-Metze, "Molecular characteristics and chromatin texture features in acute promyelotic leukemia", Diagn Pathol, 28, 7, pp.75, 2012.
8 H. S. Choi, "A Study on the Multi-View Based Computer Aided Diagnosis and 3-Dimentional Display System" The graduate school of Hanyang University, 2007.
9 J. S. Lee, "Detection of Microcalcification using Computer Aided Diagnosis in the Breast US" The graduate school of Catholic University of Pusan, 2011.
10 C. S. Kim, S. J. Ko, S. S. Kang, J. H. Kim, D. H. Kim, S. Y. Choi, "Computer-Aided Diagnosis for Liver Cirrhosis using Texture Features Information Analysis in Computed Tomography", Journal of the Korea Contents Association, 12, 4, pp.358-366, 2012.   과학기술학회마을   DOI   ScienceOn
11 J. S. Cho, H. S. Kang, H. S. Kim, S. D. Kim, "Multimedia signal processing: fundamentals and practice", 2nd edition, sungjin media, 2011.
12 H. H. Park, " A Study of Recognition for Lung Cancer using Principle Component Analysis in Chest Radiography", The graduate school of Catholic University of Pusan, 2009.
13 I. Christoyianni, A. Koutras, E. Dermatas, G. Kokkinakis, "Computer aided diagnosis of breast cancer in digitized Mammograms", Computerized Medical Imaging and Graphics, 26, 54, pp.309-319, 2002.   DOI   ScienceOn
14 D. Kontos, L. C. Ikejimba, P. R. Bakic, A. B. Troxel, E. F. Conant, A. D. Maidment, "Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment", Radiology, 261, 1, pp.80-91, 2011.   DOI
15 R. C. Gonzalez, R. E. Woods, S. L. Eddins, "Digital Image Processing using MATLAB", Prentice Hall, 2004.
16 M. Gletsos, S. G. Mougiakakou, K. S. Nikita, A. S. Nikita, D. Kelekis, "A computer-aided diagnosis system to characterize CT focal liver lesion: design and optimization of a neural network classifier", IEEE Trans Inf Technol Biomed, 7, 3, pp.153-162, 2003.   DOI
17 M. A. Heller, "Texture perception in sight and blind observers", Percept Psychophs, 45, 1, pp.49-54, 1989.   DOI
18 X. J. Chen, D. Eu, Y. He, S. Liu, "Study on application of multi-spectral image texture to discriminating rice categories base on wavlet packet and support vector machine", Guang Pu Xue Yu Guang Pu Fen Xi., 29, 1, pp.222-225, 2009.
19 D. H. Kim, S. J. Ko, S. S. Kang, J. H. Kim, C. S. Kim, "Computer-Aided Diagnosis for Pulmonary Tuberculosis using Texture Features Analysis in Digital Chest Radiography", Journal of the Korea Contents Association, 11, 11, pp.185-193, 2011.   과학기술학회마을   DOI   ScienceOn
20 S. J. Ko, J. S. Lee, S. Y. Ye, C. S. Kim, "Application of Texture Features Algorithm using Computer-Aided Diagnosis of Papillary Thyroid Cancer in the Ultrasonography", Journal of the Korea Contents Association, 13, 5, pp.303-310, 2013.   과학기술학회마을   DOI
21 J. W. Back, "The usefulness and Limitation of Breast Ultrasonography" The graduate school of Korea University, 2011.
22 J. E. Yoo, T. S. Jun, J. Y. Jeong, I. C. Im, J. S. Lee, H. H. Park, "Application of Texture Feature Analysis Algorithm used the Statistical Charaterristics in the Computed Tomography: A base on the Hepatocellular Carcinoma(HCC)", J. Korean Soc. Radiology, 7, 1, pp.9-15, 2013.   DOI
23 S. J. Kim, N. R. Y. Cho, J. H. Cha, H. K. Jeong, S. H. Lee, K. S. Cho, S. M. Kim, Y. K. Moon, "Reprducibility of Computer-Aided Detection System in Digital Mammograms", J. Korean Soc. Radiology, 52, 2, pp.137-142, 2005.   DOI