HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning
Breast cancer is the leading cancer in the world. Mammogram is a gold standard for detecting breast cancer at earlier screening because of its sensitivity. Standard grayscale mammogram images are used by expert radiologists and Computer Aided-Diagnosis (CAD) systems. Yet, this original x-ray color...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Science Publishing Corporation
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/74491/1/HARIRAYA.pdf |
| _version_ | 1825950346293280768 |
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| author | Ahmad Nazri, Azree Shahrel Agbolade, Olalekan |
| author_facet | Ahmad Nazri, Azree Shahrel Agbolade, Olalekan |
| author_sort | Ahmad Nazri, Azree Shahrel |
| collection | UPM |
| description | Breast cancer is the leading cancer in the world. Mammogram is a gold standard for detecting breast cancer at earlier screening because of its sensitivity. Standard grayscale mammogram images are used by expert radiologists and Computer Aided-Diagnosis (CAD) systems.
Yet, this original x-ray color provides little information to human radiologists and CAD systems to make decision. This binary color code thus affects sensitivity and specificity of prediction and subsequently affects accuracy. In order to enhance classifier models’ perfor-mance, this paper proposes a novel feature-level data integration method that combines features from grayscale mammogram and spec-
trum mammogram based on a deep neural network (DNN), called HARIRAYA. Pseudo-color is generated using spectrum color code to produce Spectrum mammogram from grayscale mammogram. The DNN is trained with three layers: grayscale, false-color and joint fea-ture representation layers. Empirical results show that the multi-modal DNN model has a better performance in the prediction of malig-
nant breast tissue than single-modal DNN using HARIRAYA features. |
| first_indexed | 2024-03-06T10:13:11Z |
| format | Article |
| id | upm.eprints-74491 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:13:11Z |
| publishDate | 2018 |
| publisher | Science Publishing Corporation |
| record_format | dspace |
| spelling | upm.eprints-744912020-10-17T20:34:16Z http://psasir.upm.edu.my/id/eprint/74491/ HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning Ahmad Nazri, Azree Shahrel Agbolade, Olalekan Breast cancer is the leading cancer in the world. Mammogram is a gold standard for detecting breast cancer at earlier screening because of its sensitivity. Standard grayscale mammogram images are used by expert radiologists and Computer Aided-Diagnosis (CAD) systems. Yet, this original x-ray color provides little information to human radiologists and CAD systems to make decision. This binary color code thus affects sensitivity and specificity of prediction and subsequently affects accuracy. In order to enhance classifier models’ perfor-mance, this paper proposes a novel feature-level data integration method that combines features from grayscale mammogram and spec- trum mammogram based on a deep neural network (DNN), called HARIRAYA. Pseudo-color is generated using spectrum color code to produce Spectrum mammogram from grayscale mammogram. The DNN is trained with three layers: grayscale, false-color and joint fea-ture representation layers. Empirical results show that the multi-modal DNN model has a better performance in the prediction of malig- nant breast tissue than single-modal DNN using HARIRAYA features. Science Publishing Corporation 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/74491/1/HARIRAYA.pdf Ahmad Nazri, Azree Shahrel and Agbolade, Olalekan (2018) HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning. International Journal of Engineering and Technology(UAE), 7 (4.31). 322 - 325. ISSN 2227-524X https://www.sciencepubco.com/index.php/ijet/article/view/23389 10.14419/ijet.v7i4.31.23389 |
| spellingShingle | Ahmad Nazri, Azree Shahrel Agbolade, Olalekan HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title | HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title_full | HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title_fullStr | HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title_full_unstemmed | HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title_short | HARIRAYA: a novel breast cancer pseudo-color feature for multimodal mammogram using deep learning |
| title_sort | hariraya a novel breast cancer pseudo color feature for multimodal mammogram using deep learning |
| url | http://psasir.upm.edu.my/id/eprint/74491/1/HARIRAYA.pdf |
| work_keys_str_mv | AT ahmadnazriazreeshahrel harirayaanovelbreastcancerpseudocolorfeatureformultimodalmammogramusingdeeplearning AT agboladeolalekan harirayaanovelbreastcancerpseudocolorfeatureformultimodalmammogramusingdeeplearning |