Mammographic mass classification using filter response patches

Author:

Suhail Zobia1ORCID,Hamidinekoo Azam2,Zwiggelaar Reyer2

Affiliation:

1. Punjab University College of Information Technology, University of the PunjabLahorePakistan

2. Department of Computer ScienceAberystwyth UniversityWalesSY23 3DBUK

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Reference28 articles.

1. National Health Service‐Breast Screening: ‘Professional guidance’ 31 August 2016. Available athttps://www.gov.uk/government/collections/breast‐screening‐professional‐guidance

2. Breast Cancer - The Art and Science of Early Detection with Mammography

3. Djaroudib K. Ahmed A.T. Zidani A.: ‘Textural approach for mass abnormality segmentation in mammographic images’ 2014 arXiv preprint arXiv:1412.1506

4. CADx of mammographic masses and clustered microcalcifications: A review

5. A review of automatic mass detection and segmentation in mammographic images

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1. Detection and Classification of Breast Cancer Using CNN;Transactions on Computer Systems and Networks;2022

2. Deep learning algorithm for breast masses classification in mammograms;IET Image Processing;2020-09-08

3. Characterization of mammographic masses based on local photometric attributes;Multimedia Tools and Applications;2020-05-15

4. Multi-Resolution Analysis of Edge-Texture Features for Mammographic Mass Classification;Journal of Circuits, Systems and Computers;2019-12-09

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