Quantum inspired algorithm for microcalcification detection in mammograms

Author:

Rubio YoshioORCID,Montiel OscarORCID,Sepúlveda Roberto

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference41 articles.

1. Advances in the quantum theoretical approach to image processing applications;Abura’ed;ACM Comput. Surv.,2017

2. American Cancer Society, Cancer facts and figures 2016, 2016, (http://www.cancer.org/acs/groups/content/@editorial/documents/document/acspc-044552.pdf) [Online; Accessed 5 July 2016].

3. Mammogram segmentation using maximal cell strength updation in cellular automata;Anitha;Int. J. Comput. Appl.,2014

4. Classification of mammography images based on cellular automata and haralick parameters;Benmazou;Evol. Syst.,2014

5. Consenso mexicano sobre diagnóstico y tratamiento del cáncer mamario;Cárdenas;Gac. Mex.Oncol.,2015

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3. A review on machine learning techniques for the assessment of image grading in breast mammogram;International Journal of Machine Learning and Cybernetics;2022-04-01

4. Photothermal Signature Characterization of Breast Microcalcifications Ex-Vivo by Photoacoustic Method;IFMBE Proceedings;2019-10-01

5. Breast Microcalcification Detection Algorithm Based on Contourlet and ASVM;Algorithms;2019-06-30

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