Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform

This paper proposes a method for breast cancer diagnosis in digital mammogram. The article focuses on using texture analysis based on curvelet transform for the classification of tissues. The most discriminative texture features of regions of interest are extracted and then, a classifier is buil...

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Main Authors: Brahim Belhaouari, samir, Ibrahima , faye, mohamed, eltoukhy
Format: Conference or Workshop Item
Language:English
Published: 2010
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/939/
http://scholars.utp.edu.my/id/eprint/939/1/Curvelet_texture_Statistics_UTP.pdf
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author Brahim Belhaouari, samir
Ibrahima , faye
mohamed, eltoukhy
author_facet Brahim Belhaouari, samir
Ibrahima , faye
mohamed, eltoukhy
author_sort Brahim Belhaouari, samir
building UTP Institutional Repository
collection Online Access
description This paper proposes a method for breast cancer diagnosis in digital mammogram. The article focuses on using texture analysis based on curvelet transform for the classification of tissues. The most discriminative texture features of regions of interest are extracted and then, a classifier is built. The approach consists of three steps, detecting the abnormality, classify this abnormality into one of the abnormality types and lastly distinguish between benign and malignant tumors.
first_indexed 2025-11-13T07:24:25Z
format Conference or Workshop Item
id oai:scholars.utp.edu.my:939
institution Universiti Teknologi Petronas
institution_category Local University
language English
last_indexed 2025-11-13T07:24:25Z
publishDate 2010
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:9392017-01-19T08:24:36Z http://scholars.utp.edu.my/id/eprint/939/ Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform Brahim Belhaouari, samir Ibrahima , faye mohamed, eltoukhy TK Electrical engineering. Electronics Nuclear engineering This paper proposes a method for breast cancer diagnosis in digital mammogram. The article focuses on using texture analysis based on curvelet transform for the classification of tissues. The most discriminative texture features of regions of interest are extracted and then, a classifier is built. The approach consists of three steps, detecting the abnormality, classify this abnormality into one of the abnormality types and lastly distinguish between benign and malignant tumors. 2010 Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/939/1/Curvelet_texture_Statistics_UTP.pdf Brahim Belhaouari, samir and Ibrahima , faye and mohamed, eltoukhy (2010) Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform. In: ICIAS 2010.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Brahim Belhaouari, samir
Ibrahima , faye
mohamed, eltoukhy
Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title_full Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title_fullStr Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title_full_unstemmed Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title_short Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform
title_sort breast cancer diagnosis based on texture feature extraction using curvelet transform
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/939/
http://scholars.utp.edu.my/id/eprint/939/1/Curvelet_texture_Statistics_UTP.pdf