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Medical & Biological Engineering & Computing

Erschienen in:

09.10.2018 | Original Article

Application of fractal theory and fuzzy enhancement in ultrasound image segmentation

verfasst von: Zhemin Zhuang, Naihai Lei, Alex Noel Joseph Raj, Shunmin Qiu

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 3/2019

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Abstract

The manuscript describes an ultrasound image segmentation technique based on the fractional Brownian motion (FBM) model. Here, the ultrasound images are first enhanced using a fuzzy-based technique, and later the FBM model is employed to obtain the fractal features used for segmentation. The novelty lies in combining the fuzzy-enhancement technique and FBM model, and further illustrating that fractal length-based segmentation provides better results than fractal dimension-based segmentation. Experimental results on ultrasound images of carotid artery clearly illustrate that the segmentation outputs obtained from fractal length are superior, and the high qualitative values of DSC, Precision, Recall and F₁ score (0.9617, 0.9629, 0.9653 and 0.9641 respectively), together with a low value of APD (1.9316), indicate that the proposed method is comparable to other state-of-the-art segmentation techniques.

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Titel: Application of fractal theory and fuzzy enhancement in ultrasound image segmentation
verfasst von: Zhemin Zhuang
Naihai Lei
Alex Noel Joseph Raj
Shunmin Qiu
Publikationsdatum: 09.10.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Medical & Biological Engineering & Computing / Ausgabe 3/2019
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-018-1907-z

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