Decomposition and recompilation of mammograms for breast tumour detection-Reference-Cited by-同舟云学术

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Decomposition and recompilation of mammograms for breast tumour detection

Published:2018-01-26 Issue:2 Volume:35 Page:e12243
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Yeh Jinn-Yi¹^ORCID,Chan Si-Wa²³

Affiliation:

1. Department of Management Information Systems; National Chiayi University; Chiayi Taiwan

2. Department of Medical Imageing; Taichung Tzu Chi Hospital; Taichung Taiwan

3. Graduate Institute of Biomedical Electronics and Bioinformatics; National Taiwan University; Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/exsy.12243/fullpdf

Reference21 articles.

1. Mass lesion detection using wavelet decomposition transform and support vector machine;AbuBaker;International Journal of Computer Science & Information Technology,2012

2. Robust information clustering incorporating spatial information for breast mass detection in digitized mammograms;Cao;Computer Vision and Image Understanding,2008

3. Approaches for automated detection and classification of masses in mammograms;Cheng;Pattern Recognition,2006

4. Computer-aided detection of breast cancer on mammograms: A swarm intelligence optimized wavelet neural network approach;Dheeba;Journal of Biomedical Informatics,2014

5. Adaptive Local Contrast Enhancement Combined with 2D Discrete Wavelet Transform for Mammographic Mass Detection and Classification

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Segmentation of malignant tumours in mammogram images: A hybrid approach using convolutional neural networks and connected component analysis;Expert Systems;2021-09-24

2. Considering breast density for the classification of benign and malignant mammograms;Biomedical Signal Processing and Control;2021-05

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