Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network
Identifying and treating the tumor at its early stages has become one of the major challenges faced in the area of breast imaging field since the number of women diagnosed with breast cancer has gradually increase over the years. Breast thermography has distinguished itself as a promising adjunctive...
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| Format: | Conference or Workshop Item |
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Institute of Electrical and Electronics Engineers Inc.
2016
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| _version_ | 1796862058856185856 |
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| author | Wahab, A. A. Salim, M. I. M. Yunus, J. Aziz, M. N. C. |
| author_facet | Wahab, A. A. Salim, M. I. M. Yunus, J. Aziz, M. N. C. |
| author_sort | Wahab, A. A. |
| collection | ePrints |
| description | Identifying and treating the tumor at its early stages has become one of the major challenges faced in the area of breast imaging field since the number of women diagnosed with breast cancer has gradually increase over the years. Breast thermography has distinguished itself as a promising adjunctive imaging modality to the current breast imaging standard for early detection of breast cancer. It provides additional information of underlying physiological changes of the cancerous tissues. However, this particular technique has not yet been accepted for clinical use for it is shown to be highly dependent on a trained operator and also due to the unavailability of a large clinical database for reference and classification. Therefore, this study proposed the development of Artificial Neural Network for tumor localization using thermal data obtained from the previous works. It utilized multiple features extracted from a series of numerical simulations conducted on various tissue composition breast models and were fed into the optimized ANN system of 6-8-1 network architecture with a learning rate of 0.2, an iteration rate of 20000 and a momentum constant value of 0.3. Result obtained shows that this newly developed ANN has a high performance accuracy percentage of 96.33% and 92.89% to both testing and validation data respectively. |
| first_indexed | 2024-03-05T20:05:49Z |
| format | Conference or Workshop Item |
| id | utm.eprints-73320 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:05:49Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | utm.eprints-733202017-11-20T08:42:59Z http://eprints.utm.my/73320/ Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network Wahab, A. A. Salim, M. I. M. Yunus, J. Aziz, M. N. C. QH Natural history Identifying and treating the tumor at its early stages has become one of the major challenges faced in the area of breast imaging field since the number of women diagnosed with breast cancer has gradually increase over the years. Breast thermography has distinguished itself as a promising adjunctive imaging modality to the current breast imaging standard for early detection of breast cancer. It provides additional information of underlying physiological changes of the cancerous tissues. However, this particular technique has not yet been accepted for clinical use for it is shown to be highly dependent on a trained operator and also due to the unavailability of a large clinical database for reference and classification. Therefore, this study proposed the development of Artificial Neural Network for tumor localization using thermal data obtained from the previous works. It utilized multiple features extracted from a series of numerical simulations conducted on various tissue composition breast models and were fed into the optimized ANN system of 6-8-1 network architecture with a learning rate of 0.2, an iteration rate of 20000 and a momentum constant value of 0.3. Result obtained shows that this newly developed ANN has a high performance accuracy percentage of 96.33% and 92.89% to both testing and validation data respectively. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item PeerReviewed Wahab, A. A. and Salim, M. I. M. and Yunus, J. and Aziz, M. N. C. (2016) Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network. In: IEEE Student Conference on Research and Development, SCOReD 2015, 13 - 14 Dec 2015, Kuala Lumpur, Malaysia. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966644064&doi=10.1109%2fSCORED.2015.7449383&partnerID=40&md5=c8c094a262c527c5d4a6db48c063c779 |
| spellingShingle | QH Natural history Wahab, A. A. Salim, M. I. M. Yunus, J. Aziz, M. N. C. Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title | Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title_full | Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title_fullStr | Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title_full_unstemmed | Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title_short | Tumor localization in breast thermography with various tissue compositions by using Artificial Neural Network |
| title_sort | tumor localization in breast thermography with various tissue compositions by using artificial neural network |
| topic | QH Natural history |
| work_keys_str_mv | AT wahabaa tumorlocalizationinbreastthermographywithvarioustissuecompositionsbyusingartificialneuralnetwork AT salimmim tumorlocalizationinbreastthermographywithvarioustissuecompositionsbyusingartificialneuralnetwork AT yunusj tumorlocalizationinbreastthermographywithvarioustissuecompositionsbyusingartificialneuralnetwork AT azizmnc tumorlocalizationinbreastthermographywithvarioustissuecompositionsbyusingartificialneuralnetwork |