Literature DB >> 17912970

Variable background active contour model for computer-aided delineation of nodules in thyroid ultrasound images.

Dimitris E Maroulis1, Michalis A Savelonas, Dimitris K Iakovidis, Stavros A Karkanis, Nikos Dimitropoulos.   

Abstract

This paper presents a computer-aided approach for nodule delineation in thyroid ultrasound (US) images. The developed algorithm is based on a novel active contour model, named variable background active contour (VBAC), and incorporates the advantages of the level set region-based active contour without edges (ACWE) model, offering noise robustness and the ability to delineate multiple nodules. Unlike the classic active contour models that are sensitive in the presence of intensity inhomogeneities, the proposed VBAC model considers information of variable background regions. VBAC has been evaluated on synthetic images, as well as on real thyroid US images. From the quantification of the results, two major impacts have been derived: 1) higher average accuracy in the delineation of hypoechoic thyroid nodules, which exceeds 91%; and 2) faster convergence when compared with the ACWE model.

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Year:  2007        PMID: 17912970     DOI: 10.1109/titb.2006.890018

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  4 in total

1.  Thyroid nodule recognition based on feature selection and pixel classification methods.

Authors:  Dorin Bibicu; Luminita Moraru; Anjan Biswas
Journal:  J Digit Imaging       Date:  2013-02       Impact factor: 4.056

2.  ΤND: a thyroid nodule detection system for analysis of ultrasound images and videos.

Authors:  Eystratios G Keramidas; Dimitris Maroulis; Dimitris K Iakovidis
Journal:  J Med Syst       Date:  2010-09-14       Impact factor: 4.460

3.  Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches.

Authors:  Prabal Poudel; Alfredo Illanes; Debdoot Sheet; Michael Friebe
Journal:  J Healthc Eng       Date:  2018-09-23       Impact factor: 2.682

4.  The Diagnostic Efficiency of Ultrasound Computer-Aided Diagnosis in Differentiating Thyroid Nodules: A Systematic Review and Narrative Synthesis.

Authors:  Nonhlanhla Chambara; Michael Ying
Journal:  Cancers (Basel)       Date:  2019-11-08       Impact factor: 6.639

  4 in total

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