Author, as appears in the article.: Habibi Aghdam, Hamed; Puig, Domenec; Solanas, Agusti
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: HABIBI AGHDAM, HAMED / Puig Valls, Domènec Savi / Solanas Gómez, Agustín
Keywords: 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
Abstract: 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.
Thematic Areas: 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
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: agusti.solanas@urv.cat domenec.puig@urv.cat
Author identifier: 0000-0002-4881-6215 0000-0002-0562-4205
Record's date: 2024-10-26
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.hindawi.com/journals/cmmm/2013/408595/
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Computational And Mathematical Methods In Medicine. 2013 408595-
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
Article's DOI: 10.1155/2013/408595
Entity: Universitat Rovira i Virgili
Journal publication year: 2013
Publication Type: Journal Publications
Repositori URV