Mammogram Images Thresholding for Breast Cancer Detection Using Different Thresholding Methods

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Advances in Breast Cancer Research

ISSN Print: 2168-1589
ISSN Online: 2168-1597
www.scirp.org/journal/abcr
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"Mammogram Images Thresholding for Breast Cancer Detection Using Different Thresholding Methods"
written by Moumena Al-Bayati, Ali El-Zaart,
published by Advances in Breast Cancer Research, Vol.2 No.3, 2013

has been cited by the following article(s):

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[20]	Comparative analysis of different techniques for breast cancer detection in Mammograms
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[5]	Detection of Lung Tumor Using Enhanced Image Classification 2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST), 2022 DOI:10.1109/AIST55798.2022.10064975

[6]	Prediction and classification of aerosol deposition in lung using CT scan images INDUSTRIAL, MECHANICAL AND ELECTRICAL ENGINEERING, 2022 DOI:10.1063/5.0122716

[7]	Mammogram breast cancer CAD systems for mass detection and classification: a review Multimedia Tools and Applications, 2022 DOI:10.1007/s11042-022-12332-1

[8]	Automatic Segmentation of Calcification Areas in Digital Breast Images BioMed Research International, 2022 DOI:10.1155/2022/2525433

[9]	Detection of Lung Tumor Using Enhanced Image Classification 2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST), 2022 DOI:10.1109/AIST55798.2022.10064975

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[11]	Breast Cancer Segmentation Methods: Current Status and Future Potentials BioMed Research International, 2021 DOI:10.1155/2021/9962109

[12]	Effect of image binarization thresholds on breast cancer identification in mammography images using OTSU, Niblack, Burnsen, Thepade's SBTC Intelligent Systems with Applications, 2021 DOI:10.1016/j.iswa.2021.200046

[13]	Breast Cancer Segmentation Methods: Current Status and Future Potentials BioMed Research International, 2021 DOI:10.1155/2021/9962109

[14]	Skin Cancer Segmentation with Entropy PAL MCET using Gaussian Distribution 2018 4th International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 2018 DOI:10.1109/iCATccT44854.2018.9001993

[15]	Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images Journal of Digital Imaging, 2018 DOI:10.1007/s10278-018-0075-x

[16]	Image Spectrum Segmentation for Lowpass and Highpass Filters 2018 4th International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 2018 DOI:10.1109/iCATccT44854.2018.9001919

[17]	Novel Microwave Torso Scanner for Thoracic Fluid Accumulation Diagnosis and Monitoring Scientific Reports, 2017 DOI:10.1038/s41598-017-00436-w

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[19]	Proceedings of ELM-2015 Volume 1 Proceedings in Adaptation, Learning and Optimization, 2016 DOI:10.1007/978-3-319-28397-5_12

[20]	Thresholding methods review for microcalcifications segmentation on mammography images in obvious, subtle, and cluster categories 2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 2016 DOI:10.1109/ICEEE.2016.7751192

[21]	ANN based detection of Breast Cancer in mammograph images 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), 2016 DOI:10.1109/ICPEICES.2016.7853734

[22]	Detection of Breast cancer with Hybrid image segmentation and Otsu's thresholding 2015 International Conference on Computing and Network Communications (CoCoNet), 2015 DOI:10.1109/CoCoNet.2015.7411244

[23]	Automatic Segmentation of the Left Ventricle in Cardiac MRI Using Local Binary Fitting Model and Dynamic Programming Techniques PLoS ONE, 2014 DOI:10.1371/journal.pone.0114760

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