IEEE Transactions on Information Technology in Biomedicine · 2007 · 91 citations · 17 references
MedicineBiomedical EngineeringRadiologyDiagnostic ImagingUltrasonographyUltrasoundComputer-aided DiagnosisMedical ImagingThyroid ImagingThyroid UltrasonographyThyroid UltrasoundUltrasound ImagingAccuracyActive Contour ModelsActive ContoursBackground Noise RobustnessConvergenceNoise RobustnessRobustness To NoiseThyroid Nodule Diagnostic Algorithms
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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Tony F. Chan, Luminita A. Vese · IEEE Transactions on Image Processing · 2001 · 10.3K citations
Vicent Caselles, Ron Kimmel, Guillermo Sapiro · International Journal of Computer Vision · 1997 · 5.2K citations