Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound
Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-H...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1100/2012/870869 |
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| author | R. Jurkonis A. Janušauskas V. Marozas D. Jegelevičius S. Daukantas M. Patašius A. Paunksnis A. Lukoševičius |
| author_facet | R. Jurkonis A. Janušauskas V. Marozas D. Jegelevičius S. Daukantas M. Patašius A. Paunksnis A. Lukoševičius |
| author_sort | R. Jurkonis |
| collection | DOAJ |
| description | Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation. |
| format | Article |
| id | doaj-art-d128c8da4dcd45fa88c99e3e7240b393 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-d128c8da4dcd45fa88c99e3e7240b3932025-02-03T06:12:36ZengWileyThe Scientific World Journal1537-744X2012-01-01201210.1100/2012/870869870869Algorithms and Results of Eye Tissues Differentiation Based on RF UltrasoundR. Jurkonis0A. Janušauskas1V. Marozas2D. Jegelevičius3S. Daukantas4M. Patašius5A. Paunksnis6A. Lukoševičius7Biomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaJSC “Stratelus”, Naugarduko Street 3, 03231 Vilnius, LithuaniaBiomedical Engineering Institute, Kaunas University of Technology, Studentu Street 65, 51369 Kaunas, LithuaniaAlgorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation.http://dx.doi.org/10.1100/2012/870869 |
| spellingShingle | R. Jurkonis A. Janušauskas V. Marozas D. Jegelevičius S. Daukantas M. Patašius A. Paunksnis A. Lukoševičius Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound The Scientific World Journal |
| title | Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound |
| title_full | Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound |
| title_fullStr | Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound |
| title_full_unstemmed | Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound |
| title_short | Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound |
| title_sort | algorithms and results of eye tissues differentiation based on rf ultrasound |
| url | http://dx.doi.org/10.1100/2012/870869 |
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