Literature DB >> 20163793

A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram.

Mohamed Meselhy Eltoukhy1, Ibrahima Faye, Brahim Belhaouari Samir.   

Abstract

This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant. 2010 Elsevier Ltd. All rights reserved.

Entities:  

Mesh：

Year:  2010        PMID： 20163793     DOI： 10.1016/j.compbiomed.2010.02.002

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN： 0010-4825            Impact factor:   4.589


  9 in total

1.  Three-Dimensional Texture Feature Analysis of Pulmonary Nodules in CT Images: Lung Cancer Predictive Models Based on Support Vector Machine Classifier.

Authors:  Ni Gao; Sijia Tian; Xia Li; Jian Huang; Jingjing Wang; Sipeng Chen; Yuan Ma; Xiangtong Liu; Xiuhua Guo
Journal:  J Digit Imaging       Date:  2020-04       Impact factor: 4.056

2.  An evaluation of image descriptors combined with clinical data for breast cancer diagnosis.

Authors:  Daniel C Moura; Miguel A Guevara López
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-04-13       Impact factor: 2.924

3.  Contourlet textual features: improving the diagnosis of solitary pulmonary nodules in two dimensional CT images.

Authors:  Jingjing Wang; Tao Sun; Ni Gao; Desmond Dev Menon; Yanxia Luo; Qi Gao; Xia Li; Wei Wang; Huiping Zhu; Pingxin Lv; Zhigang Liang; Lixin Tao; Xiangtong Liu; Xiuhua Guo
Journal:  PLoS One       Date:  2014-09-24       Impact factor: 3.240

4.  Three-Class Mammogram Classification Based on Descriptive CNN Features.

Authors:  M Mohsin Jadoon; Qianni Zhang; Ihsan Ul Haq; Sharjeel Butt; Adeel Jadoon
Journal:  Biomed Res Int       Date:  2017-01-15       Impact factor: 3.411

5.  LRSCnet: Local Reference Semantic Code learning for breast tumor classification in ultrasound images.

Authors:  Guang Zhang; Yanwei Ren; Xiaoming Xi; Delin Li; Jie Guo; Xiaofeng Li; Cuihuan Tian; Zunyi Xu
Journal:  Biomed Eng Online       Date:  2021-12-17       Impact factor: 2.819

6.  Classification of Multiclass Histopathological Breast Images Using Residual Deep Learning.

Authors:  Mohamed Meselhy Eltoukhy; Khalid M Hosny; Mohamed A Kassem
Journal:  Comput Intell Neurosci       Date:  2022-10-10

7.  Computer-aided diagnosis for early-stage lung cancer based on longitudinal and balanced data.

Authors:  Tao Sun; Regina Zhang; Jingjing Wang; Xia Li; Xiuhua Guo
Journal:  PLoS One       Date:  2013-05-15       Impact factor: 3.240

8.  Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

Authors:  Kendra A Batchelder; Aaron B Tanenbaum; Seth Albert; Lyne Guimond; Pierre Kestener; Alain Arneodo; Andre Khalil
Journal:  PLoS One       Date:  2014-09-15       Impact factor: 3.240

9.  Local Binary Patterns Descriptor Based on Sparse Curvelet Coefficients for False-Positive Reduction in Mammograms.

Authors:  Meenakshi M Pawar; Sanjay N Talbar; Akshay Dudhane
Journal:  J Healthc Eng       Date:  2018-09-25       Impact factor: 2.682
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.