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RSF model optimization and its application to brain tumor segmentation in MRI / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 265-271, 2013.
Article in Chinese | WPRIM | ID: wpr-234666
ABSTRACT
Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Pathology / Algorithms / Image Processing, Computer-Assisted / Brain Neoplasms / Magnetic Resonance Imaging / Diagnosis / Methods / Models, Theoretical Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2013 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Pathology / Algorithms / Image Processing, Computer-Assisted / Brain Neoplasms / Magnetic Resonance Imaging / Diagnosis / Methods / Models, Theoretical Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2013 Type: Article