Improving Breast Mass Segmentation in Local Dense Background: an Entropy based Optimization of Statistical Region Merging Method

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    2 Citations (Scopus)

    Abstract

    In this paper, an optimization algorithm, utilizing a component measure of entropy, is developed for automatically tuning segmentation of mammograms by the Statistical Region Merging technique. The aim of this paper is to improve the mass segmentation in dense backgrounds. The proposed algorithm is tested on a database of 89 mammograms of which 41 have masses localized in dense background and 48 have masses in non-dense background. The algorithm performance is evaluated in conjunction with six standard enhancement techniques: Adjustable Histogram Equalization, Unsharp Masking, Neutrosophy based enhancement, standard CLAHE, Adaptive Clip Limit CLAHE based on standard deviation and Adaptive Clip Limit CLAHE based on standard entropy measure. For a comparison study, same experiments are performed using Fuzzy C-means Clustering technique. The experimental results show that the automatic tuning of SRM segmentation has the potential to produce an accurate segmentation of masses located in dense background while not compromising the performance on masses located in non-dense background.

    Original languageEnglish
    Title of host publicationBreast Imaging - 13th International Workshop, IWDM 2016, Proceedings
    Subtitle of host publication13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, Proceedings
    EditorsAnders Tingberg, Kristina Lang, Pontus Timberg
    PublisherSpringer
    Pages635-642
    Number of pages8
    ISBN (Electronic)978-3-319-41546-8
    ISBN (Print)978-3-319-41545-1
    DOIs
    Publication statusPublished - 1 Jan 2016
    Event13th International Workshop on Breast Imaging, IWDM 2016 -
    Duration: 19 Jun 2016 → …

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Number9699
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference13th International Workshop on Breast Imaging, IWDM 2016
    Period19/06/16 → …

    Keywords

    • Dense background
    • Enhancement
    • Entropy
    • Mammography
    • Segmentation
    • Statistical region merging

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