NDLI: Two-step evidential fusion approach for accurate breast region segmentation in mammograms

Content Provider	IET Digital Library
Author	Lajili, Rihab Kalti, Karim Touil, Asma Solaiman, Basel Amara, Najoua Essoukri Ben
Abstract	In mammograms, the breast skin line often appears ambiguous and poorly defined. This is mainly due to the breast organ compression during the image acquisition process along with the inherent low density of the tissue in that area. The accurate delimitation of the breast region becomes a challenging task to conventional segmentation techniques. In this study, the authors propose a new segmentation approach allowing to overcome this challenge. This approach is based on the application of two complementary segmentation techniques exploring each, respectively, the grey-scale intensities and the local-homogeneity domains. The knowledge resulting from each segmentation technique is considered as a knowledge source and is modelled using the belief functions formalism. The two considered knowledge sources are then fused using an iterative process. The obtained results show the efficiency of the proposed evidential approach especially in terms of ambiguity removal and decision quality improvement for accurate breast border delimitation (which is often under-segmented and assimilated to the background by most of the existing segmentation techniques).
Starting Page	1972
Ending Page	1982
Page Count	11
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 11, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5325
Journal	IET Image Processing
Publisher Date	2018-07-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Breast Region Segmentation Ambiguity Removal Belief Function Formalism Biology And Medical Computing Biomedical Imaging/measurement Breast Organ Compression Breast Region Delimitation Breast Skin Line Complementary Segmentation Technique Computer Vision And Image Processing Technique Decision Quality Improvement Grey-scale Intensities Image Acquisition Process Image Fusion Image Segmentation Interpolation And Function Approximation Iterative Method Iterative Process Knowledge Source Local-homogeneity Domain Mammograms Mammography Medical Image Processing Numerical Analysis Numerical Approximation And Analysis Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Radiography And Computed Tomography Sensor Fusion Two-step Evidential Fusion Approach X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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