A novel image enhancement methodology for full field digital mammography

He, W, Kibiro, M, Juette, A, Denton, ERE, Hogg, P ORCID: https://orcid.org/0000-0002-6506-0827 and Zwiggelaar, R 2014, 'A novel image enhancement methodology for full field digital mammography' , in: Breast Imaging : 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings , Springer International Publishing, pp. 650-657.

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During breast screening it is necessary and essential to compress the breast with a compression paddle, in order to obtain a clear mammographic image. The quality of the image has a direct correlation with the accuracy of mammogram reading, which in turn could affect radiologist’s interpretation. Clinical observation has indicated that breast compression may have a side effect on image quality during the image acquisition and can result in unexpected variations in texture and intensity appearances, between breast tissue near the skinline and the rest of the breast. Within computer aided mammography, such variations increase the difficulty in breast tissue modelling and can be detrimental to image analysis, leading to incorrect prompts which can have an impact on sensitivity and specificity of screening mammography. We present an automatic image enhancement approach, in which both Cranio Caudal and Medio-Lateral Oblique views are utilised. We estimate the relative breast thickness ratio at a given projection location in order to alter/correct an inconsistent intensity distribution as a means of improving mammographic image quality. Our dataset consists of 360 full field digital mammographic images was used in a quantitative and qualitative evaluation. Visual assessment indicated good and consistent intensity variation over the processed images, whilst texture information (breast parenchymal patterns) was preserved and/or enhanced. By improving the consistency of the intensity distribution on the mammographic images, the developed method has demonstrated a potential benefit in density based mammographic segmentation and risk assessment. This in turn can be found useful in computer aided mammography, and is beneficial in a clinical setting by aiding screening radiologists in the process of decision making.

Item Type: Book Section
Schools: Schools > School of Health Sciences
Publisher: Springer International Publishing
ISBN: 9783319078861
ISSN: 0302-9743
Related URLs:
Depositing User: RL Shaw
Date Deposited: 26 Oct 2016 15:20
Last Modified: 27 Aug 2021 23:30
URI: https://usir.salford.ac.uk/id/eprint/40472

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