SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM
Computer Aided Diagnosis (CAD) system plays an important role in the medical field. It helps to reduce the mortality rate due to the early diagnosis of cancers. Photographing the changes in the internal breast structure due to the formation of masses and MicroCalcifications (MC) for the detection of...
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| Format: | Article |
| Language: | English |
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XLESCIENCE
2016-06-01
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| Series: | International Journal of Advances in Signal and Image Sciences |
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| Online Access: | https://xlescience.org/index.php/IJASIS/article/view/9 |
| _version_ | 1818388253076619264 |
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| author | Leena Jasmine J S |
| author_facet | Leena Jasmine J S |
| author_sort | Leena Jasmine J S |
| collection | DOAJ |
| description | Computer Aided Diagnosis (CAD) system plays an important role in the medical field. It helps to reduce the mortality rate due to the early diagnosis of cancers. Photographing the changes in the internal breast structure due to the formation of masses and MicroCalcifications (MC) for the detection of breast cancer is known as mammography. It uses X-rays to capture the breast tissues. In this paper, the breast tumour in the mammogram is classified into benign or malignant classes using surfacelet transform. First, the Region Of Interest (ROI) is extracted and then enhanced using histogram equalization. The enhanced mammogram ROI is subjected to surfacelet transform and features are extracted using surfacelet coefficients. Then the features are fed to Decision Tree (DT) classifier for two class prediction; benign or malignant. |
| first_indexed | 2024-12-14T04:22:54Z |
| format | Article |
| id | doaj.art-209613a8754a4b82a57bcc18985f0ac7 |
| institution | Directory Open Access Journal |
| issn | 2457-0370 |
| language | English |
| last_indexed | 2024-12-14T04:22:54Z |
| publishDate | 2016-06-01 |
| publisher | XLESCIENCE |
| record_format | Article |
| series | International Journal of Advances in Signal and Image Sciences |
| spelling | doaj.art-209613a8754a4b82a57bcc18985f0ac72022-12-21T23:17:17ZengXLESCIENCEInternational Journal of Advances in Signal and Image Sciences2457-03702016-06-0121111810.29284/ijasis.2.1.2016.11-189SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEMLeena Jasmine J SComputer Aided Diagnosis (CAD) system plays an important role in the medical field. It helps to reduce the mortality rate due to the early diagnosis of cancers. Photographing the changes in the internal breast structure due to the formation of masses and MicroCalcifications (MC) for the detection of breast cancer is known as mammography. It uses X-rays to capture the breast tissues. In this paper, the breast tumour in the mammogram is classified into benign or malignant classes using surfacelet transform. First, the Region Of Interest (ROI) is extracted and then enhanced using histogram equalization. The enhanced mammogram ROI is subjected to surfacelet transform and features are extracted using surfacelet coefficients. Then the features are fed to Decision Tree (DT) classifier for two class prediction; benign or malignant.https://xlescience.org/index.php/IJASIS/article/view/9mammogram, cad, surfacelet transform, decision tree |
| spellingShingle | Leena Jasmine J S SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM International Journal of Advances in Signal and Image Sciences mammogram, cad, surfacelet transform, decision tree |
| title | SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM |
| title_full | SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM |
| title_fullStr | SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM |
| title_full_unstemmed | SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM |
| title_short | SURFACELET TRANSFORM BASED MAMMOGRAM CLASSIFICATION SYSTEM |
| title_sort | surfacelet transform based mammogram classification system |
| topic | mammogram, cad, surfacelet transform, decision tree |
| url | https://xlescience.org/index.php/IJASIS/article/view/9 |
| work_keys_str_mv | AT leenajasminejs surfacelettransformbasedmammogramclassificationsystem |