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A probabilistic approach for breast boundary extraction in mammograms

  • Datos identificativos

    Identificador: imarina:9285357
    Autores:
    Habibi Aghdam, HamedPuig, DomenecSolanas, Agusti
    Resumen:
    The extraction of the breast boundary is crucial to perform further analysis of mammogram. Methods to extract the breast boundary can be classified into two categories: methods based on image processing techniques and those based on models. The former use image transformation techniques such as thresholding, morphological operations, and region growing. In the second category, the boundary is extracted using more advanced techniques, such as the active contour model. The problem with thresholding methods is that it is a hard to automatically find the optimal threshold value by using histogram information. On the other hand, active contour models require defining a starting point close to the actual boundary to be able to successfully extract the boundary. In this paper, we propose a probabilistic approach to address the aforementioned problems. In our approach we use local binary patterns to describe the texture around each pixel. In addition, the smoothness of the boundary is handled by using a new probability model. Experimental results show that the proposed method reaches 38% and 50% improvement with respect to the results obtained by the active contour model and threshold-based methods respectively, and it increases the stability of the boundary extraction process up to 86%. © 2013 Hamed Habibi Aghdam et al.
  • Otros:

    Autor según el artículo: Habibi Aghdam, Hamed; Puig, Domenec; Solanas, Agusti
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: HABIBI AGHDAM, HAMED / Puig Valls, Domènec Savi / Solanas Gómez, Agustín
    Palabras clave: X ray screens Thresholding methods Thresholding method Textures Texture probability Support vector machine Statistics and numerical data Statistics Statistical model Smoothness probability Radiography Radiographic image interpretation, computer-assisted Procedures Probability modeling Probability Probabilistic approaches Prior probability Pectoral muscle Pathology Morphological operations Models, statistical Methodology Medical imaging Mathematical morphology Mathematical model Mammography Local binary patterns Image transformations Image segmentation Image processing technique Image processing Image analysis Humans Human Histogram information Histogram Hidden markov model Fourier transformation Female Factual database Extraction Databases, factual Computer assisted diagnosis Breast tumor Breast neoplasms Breast boundary extraction Breast Artificial intelligence Article Anatomic model Anatomic landmark Algorithms Algorithm Active contour model
    Resumen: The extraction of the breast boundary is crucial to perform further analysis of mammogram. Methods to extract the breast boundary can be classified into two categories: methods based on image processing techniques and those based on models. The former use image transformation techniques such as thresholding, morphological operations, and region growing. In the second category, the boundary is extracted using more advanced techniques, such as the active contour model. The problem with thresholding methods is that it is a hard to automatically find the optimal threshold value by using histogram information. On the other hand, active contour models require defining a starting point close to the actual boundary to be able to successfully extract the boundary. In this paper, we propose a probabilistic approach to address the aforementioned problems. In our approach we use local binary patterns to describe the texture around each pixel. In addition, the smoothness of the boundary is handled by using a new probability model. Experimental results show that the proposed method reaches 38% and 50% improvement with respect to the results obtained by the active contour model and threshold-based methods respectively, and it increases the stability of the boundary extraction process up to 86%. © 2013 Hamed Habibi Aghdam et al.
    Áreas temáticas: Saúde coletiva Química Modeling and simulation Medicine (miscellaneous) Medicina veterinaria Medicina ii Medicina i Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar Immunology and microbiology (miscellaneous) Immunology and microbiology (all) General medicine General immunology and microbiology General biochemistry,genetics and molecular biology Engenharias iv Engenharias iii Ciências biológicas i Ciência da computação Biochemistry, genetics and molecular biology (miscellaneous) Biochemistry, genetics and molecular biology (all) Astronomia / física Applied mathematics Administração pública e de empresas, ciências contábeis e turismo
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: agusti.solanas@urv.cat domenec.puig@urv.cat
    Identificador del autor: 0000-0002-4881-6215 0000-0002-0562-4205
    Fecha de alta del registro: 2024-10-26
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.hindawi.com/journals/cmmm/2013/408595/
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Computational And Mathematical Methods In Medicine. 2013 408595-
    Referencia de l'ítem segons les normes APA: Habibi Aghdam, Hamed; Puig, Domenec; Solanas, Agusti (2013). A probabilistic approach for breast boundary extraction in mammograms. Computational And Mathematical Methods In Medicine, 2013(), 408595-. DOI: 10.1155/2013/408595
    DOI del artículo: 10.1155/2013/408595
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2013
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Applied Mathematics,Biochemistry, Genetics and Molecular Biology (Miscellaneous),Immunology and Microbiology (Miscellaneous),Mathematical & Computational Biology,Medicine (Miscellaneous),Modeling and Simulation
    X ray screens
    Thresholding methods
    Thresholding method
    Textures
    Texture probability
    Support vector machine
    Statistics and numerical data
    Statistics
    Statistical model
    Smoothness probability
    Radiography
    Radiographic image interpretation, computer-assisted
    Procedures
    Probability modeling
    Probability
    Probabilistic approaches
    Prior probability
    Pectoral muscle
    Pathology
    Morphological operations
    Models, statistical
    Methodology
    Medical imaging
    Mathematical morphology
    Mathematical model
    Mammography
    Local binary patterns
    Image transformations
    Image segmentation
    Image processing technique
    Image processing
    Image analysis
    Humans
    Human
    Histogram information
    Histogram
    Hidden markov model
    Fourier transformation
    Female
    Factual database
    Extraction
    Databases, factual
    Computer assisted diagnosis
    Breast tumor
    Breast neoplasms
    Breast boundary extraction
    Breast
    Artificial intelligence
    Article
    Anatomic model
    Anatomic landmark
    Algorithms
    Algorithm
    Active contour model
    Saúde coletiva
    Química
    Modeling and simulation
    Medicine (miscellaneous)
    Medicina veterinaria
    Medicina ii
    Medicina i
    Mathematical & computational biology
    Matemática / probabilidade e estatística
    Interdisciplinar
    Immunology and microbiology (miscellaneous)
    Immunology and microbiology (all)
    General medicine
    General immunology and microbiology
    General biochemistry,genetics and molecular biology
    Engenharias iv
    Engenharias iii
    Ciências biológicas i
    Ciência da computação
    Biochemistry, genetics and molecular biology (miscellaneous)
    Biochemistry, genetics and molecular biology (all)
    Astronomia / física
    Applied mathematics
    Administraçã
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