Active Contour Extension Basing on Haralick Texture Features, Multi-gene Genetic Programming, and Block Matching to Segment Thyroid in 3D Ultrasound Images-Reference-Cited by-同舟云学术

Active Contour Extension Basing on Haralick Texture Features, Multi-gene Genetic Programming, and Block Matching to Segment Thyroid in 3D Ultrasound Images

Published:2022-09-29 Issue:2 Volume:48 Page:2429-2440
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Benabdallah Fatma Zohra^ORCID,Djerou Leila

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

https://link.springer.com/content/pdf/10.1007/s13369-022-07286-3.pdf

Reference49 articles.

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2. Prabal, P.; Alfredo, I.; Elmer, A.J.G.; Nazila, E.; Sathish, B.; Michael, F.: Thyroid ultrasound texture classification using autoregressive features in conjunction with machine learning approaches. IEEE Access 7, 79354–79365 (2019)

3. Zhao, J.; Zheng, W.; Zhang, L.; Tian, H.: Segmentation of ultrasound images of thyroid nodule for assisting fine needle aspiration cytology. Health Inf. Sci. Syst. 1(1), 1–12 (2013)

4. Ma, J.; Wu, F.; Jiang, T.; Zhu, J.; Kong, D.: Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images. Med. Phys. 44(5), 1678–1691 (2017)

5. Noble, J.A.; Boukerroui, D.: Ultrasound image segmentation: a survey. IEEE Trans. Med. Imaging 25(8), 987–1010 (2006)

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